Careers at F7D8749A 72D6 407C Bf98 292Ea630C73A

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Cloud Engineering builds and operates the infrastructure and environments that support Shield AI’s software products and platforms. As a Staff Cloud Engineer, you will design, build, and operate the cloud infrastructure and environments used to develop, test, integrate, and host Shield AI’s software products and platforms. You will work across AWS infrastructure, shared development environments, and supporting platform services to improve how these systems are provisioned, operated, and maintained. This is a hands-on engineering role focused on infrastructure automation, reliability, and operational stability. You will troubleshoot problems across infrastructure and services, improve existing systems, and work with engineering teams to build infrastructure that meets their development and integration needs. What You'll Do Design, build, and operate AWS infrastructure and shared development and integration environments Build and maintain infrastructure using Terraform and other infrastructure-as-code tools Automate environment provisioning, configuration, lifecycle management, and other recurring infrastructure tasks Build and operate infrastructure supporting containerized applications and workloads Establish and improve observability across cloud infrastructure and supporting services Diagnose and resolve infrastructure and environment issues across products and platform services. Improve the reliability and consistency of shared environments and platform services. Partner with Cybersecurity, Infosec, and Enterprise Ops to implement infrastructure and access controls that meet security and compliance requirements Monitor resource utilization and identify opportunities to improve infrastructure cost and capacity Required Qualifications Experience supporting shared cloud infrastructure across multiple products or engineering teams Experience with Kubernetes or other container orchestration platforms Experience with infrastructure as code tooling Experience designing automated or ephemeral environment lifecycle management Experience operating infrastructure in regulated or compliance-driven environments Experience implementing cloud IAM, access controls, and infrastructure security requirements Experience with AWS cost management, capacity planning, or resource optimization #LI-DM2 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Hivemind is looking for an experienced SRE lead to help drive the establishment of our SRE function. As the SRE lead, you will establish and mature the reliability practices used across our cloud infrastructure and platform services. You will work with Cloud Engineering and product teams to define reliability targets, improve observability, and ensure that production systems can be operated and recovered predictably. This is a deeply technical, hands-on role. You will investigate complex failures, improve the systems and tooling used to operate our platforms, and turn lessons from incidents into engineering improvements. You will provide technical leadership for reliability engineering, helping teams adopt practices that improve system health without adding unnecessary process. You will act as a thought-leader and mentor within the Cloud Engineering and Reliability teams to level up teammates and encourage building with a reliability-first mindset. What You'll Do: Define and implement SLIs, SLOs, and other measures of service reliability Build and improve monitoring, alerting, logging, and tracing for infrastructure and platform services Lead technical response to complex incidents and drive root-cause analysis through resolution Identify recurring failure modes and work with engineering teams to eliminate them Improve system resilience through automation, testing, capacity planning, and failure recovery Develop tooling and automation that reduces manual operational work Partner with product and platform teams to incorporate reliability requirements into system design Establish incident response practices that improve detection, diagnosis, communication, and recovery Mentor product engineers and drive adoption of strong reliability and operational practices Mentor teammates in SRE and Cloud Engineering Define and manage short-and-long term SRE roadmap, distributing work across teammates Required Qualifications: 7+ years of experience in SRE, software engineering, infrastructure engineering, or related fields Experience operating production services with defined availability and reliability requirements Experience implementing SLIs, SLOs, monitoring, alerting, and incident response practices Experience designing and operating infrastructure in AWS or another major cloud environment Experience with infrastructure-as-code and automated infrastructure provisioning Experience supporting containerized applications and distributed systems Experience developing operational tooling or automation using Python, Go, or a similar language Ability to diagnose complex failures across applications, infrastructure, networking, and dependent services Experience leading incident response and root-cause analysis across engineering teams Experience leading and executing on technical vision of a team over multi-quarter timelines Preferred Qualifications: Experience establishing or maturing an SRE function within an engineering organization Experience with Kubernetes and cloud-native observability systems Experience operating systems in regulated or compliance-driven environments Experience with capacity planning, performance analysis, and cloud cost management Background supporting shared infrastructure across multiple products or engineering organizations Experience with building roadmaps in ticketing systems Experience acting as a mentor for other engineers Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Hivemind is looking for an experienced SRE lead to help drive the establishment of our SRE function. As the SRE Lead, you will establish and mature the reliability practices used across our cloud infrastructure and platform services. You will work with Cloud Engineering and product teams to define reliability targets, improve observability, and ensure that production systems can be operated and recovered predictably. This is a deeply technical, hands-on role. You will investigate complex failures, improve the systems and tooling used to operate our platforms, and turn lessons from incidents into engineering improvements. You will provide technical leadership for reliability engineering, helping teams adopt practices that improve system health without adding unnecessary process. You will act as a thought-leader and mentor within the Cloud Engineering and Reliability teams to level up teammates and encourage building with a reliability-first mindset. What You'll Do: Define and implement SLIs, SLOs, and other measures of service reliability Build and improve monitoring, alerting, logging, and tracing for infrastructure and platform services Lead technical response to complex incidents and drive root-cause analysis through resolution Identify recurring failure modes and work with engineering teams to eliminate them Improve system resilience through automation, testing, capacity planning, and failure recovery Develop tooling and automation that reduces manual operational work Partner with product and platform teams to incorporate reliability requirements into system design Establish incident response practices that improve detection, diagnosis, communication, and recovery Mentor product engineers and drive adoption of strong reliability and operational practices Mentor teammates in SRE and Cloud Engineering Define and manage short-and-long term SRE roadmap, distributing work across teammates Required Qualifications: 7+ years of experience in SRE, software engineering, infrastructure engineering, or related fields Experience operating production services with defined availability and reliability requirements Experience implementing SLIs, SLOs, monitoring, alerting, and incident response practices Experience designing and operating infrastructure in AWS or another major cloud environment Experience with infrastructure-as-code and automated infrastructure provisioning Experience supporting containerized applications and distributed systems Experience developing operational tooling or automation using Python, Go, or a similar language Ability to diagnose complex failures across applications, infrastructure, networking, and dependent services Experience leading incident response and root-cause analysis across engineering teams Experience leading and executing on technical vision of a team over multi-quarter timelines Preferred Qualifications: Experience establishing or maturing an SRE function within an engineering organization Experience with Kubernetes and cloud-native observability systems Experience operating systems in regulated or compliance-driven environments Experience with capacity planning, performance analysis, and cloud cost management Background supporting shared infrastructure across multiple products or engineering organizations Experience with building roadmaps in ticketing systems Experience acting as a mentor for other engineers Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Hivemind is looking for an experienced Senior or Staff Software Engineer to join our Developer Experience Engineering team. The Developer Experience team owns the tools, platforms, and practices that shape how engineers build software for Hivemind. This includes local development environments, devcontainers, our internal developer platform, project templates, and approaches that enable co-development and inner-source collaboration across engineering teams. You will build tools and paved paths that make development faster, more consistent, and more reliable. A near-term focus for this role will be bringing agentic AI capabilities into our developer tools and workflows in ways that deliver meaningful, measurable value to engineers. This is a hands-on engineering role with broad organizational impact. You will partner directly with developers, identify recurring sources of friction, turn ambiguous needs into durable solutions, and drive adoption through documentation, advocacy, and close collaboration. You will care about engineering productivity and use signals such as DORA metrics and developer feedback to guide priorities and measure outcomes. This position may be filled at the Senior or Staff level based on the candidate’s experience, demonstrated technical leadership, and scope of impact. What you'll do: Design, build, and operate tools and platforms that improve the end-to-end Hivemind developer experience Advance local development workflows, devcontainers, internal developer platforms, project templates, and other reusable engineering capabilities Bring agentic AI capabilities into developer tools and workflows, evaluating opportunities and turning promising ideas into reliable, practical solutions Partner with engineering teams to understand developer needs, identify recurring friction, and create paved paths that improve productivity without limiting appropriate flexibility Enable co-development and inner-source collaboration through accessible tooling, documentation, standards, and contribution practices Drive adoption of developer tools by working closely with engineers, gathering feedback, providing guidance, and clearly communicating their value Own solutions through discovery, design, implementation, testing, deployment, operation, and continuous improvement Use DORA metrics, developer feedback, adoption data, and other signals to understand outcomes and guide investment Contribute to technical direction through design reviews, architectural decisions, thoughtful tradeoffs, and collaboration across engineering teams At the Staff level, lead cross-team initiatives, establish longer-term technical direction, and influence how Hivemind approaches developer productivity at organizational scale Required qualifications: 4+ years of software engineering experience or equivalent practical experience Demonstrated technical judgment in the design and operation of developer tools, platforms, backend services, APIs, distributed systems, or related production software Experience owning software from initial design through deployment, operation, adoption, and continuous improvement Systems thinking and the ability to turn recurring or ambiguous developer needs into coherent, reusable solutions Strong customer orientation toward internal developers and an interest in understanding and improving how engineering work gets done Effective collaboration and communication across engineering teams and organizational stakeholders Ability to advocate for new tools and practices, incorporate feedback, and build adoption through influence Experience with AWS and cloud-native development practices Experience with Git, GitLab, Backstage, or similar developer-platform technologies Preferred qualifications: For Staff-level consideration, a demonstrated record of leading technically complex, cross-team initiatives and shaping technical direction beyond an immediate team Experience building or operating internal developer platforms, developer portals, development environments, or reusable engineering frameworks Experience applying AI or agentic systems to software development tools and workflows Proficiency in one or more relevant languages, such as Python, Go, JavaScript, or TypeScript/Node.js Experience with devcontainers, project scaffolding, service templates, or standardized local development environments Experience enabling inner-source development or contribution across team boundaries Familiarity with DORA metrics, developer productivity measurement, and qualitative developer-experience research #LI-DM2 #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Hivemind is looking for an experienced Full Stack Software Engineer to join our Shared Services Engineering team. The Shared Services team builds and operates common services, SDKs, APIs, and customer-facing applications that connect Shield’s products. These capabilities reduce duplicated engineering and help create a consistent Shield experience across product types. You will work across the stack, from customer-facing web applications to backend services and product integrations. You will partner with product and engineering teams to understand shared needs, turn ambiguous problems into durable solutions, and own your work from design through production operation. This is a product-oriented engineering role with meaningful technical ownership. You will help shape new capabilities, contribute to architectural decisions, and build secure, reliable systems for external customers and internal engineering teams. What you'll do: Design, build, and operate full-stack applications, backend services, SDKs, and APIs Contribute to shared authentication, telemetry integrations, the Customer Support Portal, and future public telemetry APIs Partner with product and engineering teams to understand shared needs and develop reusable capabilities Establish secure, reliable, documented, and versioned interfaces for internal engineering teams and external customers Own solutions through design, implementation, testing, deployment, and production support Contribute to technical direction through design reviews, thoughtful tradeoffs, and collaboration with other engineers Required qualifications: 4+ years of software engineering experience or equivalent practical experience Demonstrated technical judgment in the design and operation of full-stack applications, backend services, APIs, or distributed systems Systems thinking and the ability to turn recurring or ambiguous needs into coherent, reusable solutions Track record of owning production software from initial design through operation and continuous improvement Effective collaboration and communication across engineering, product, and organizational stakeholders Preferred qualifications: Experience creating shared capabilities adopted across multiple products or engineering teams Depth in one or more relevant domains, such as identity and authentication, public APIs and SDKs, or OpenTelemetry and high-volume telemetry data Experience building modern web applications and the backend services that support them Experience building and operating secure, reliable software in regulated or compliance-driven environments #LI-DM2 #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . This position is ideal for an individual who thrives on solving complex integration challenges that span hardware, software, and systems engineering. A successful candidate will be skilled at deploying autonomy solutions onto unmanned platforms, preparing systems for flight, and troubleshooting mission-critical issues in both lab and field environments. The role is highly dynamic, requiring hands-on experience, strong systems thinking, and the ability to operate effectively in fast-paced, real-world test conditions. Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Flight Integration Engineers are essential to bridging the gap between R&D and deployment, ensuring that autonomous systems function reliably and effectively when and where they are needed most. What you'll do: System Integration & Deployment — Integrate autonomy software onto unmanned aircraft systems, ensuring seamless operation across onboard compute, sensors, and control interfaces. Pre-flight Preparation — Own the build, configuration, and validation process for flight-ready systems; coordinate hardware/software compatibility and mission readiness. On-site Flight Test Support — Travel to test sites and support live flight operations, including safety checks, system bring-up, and troubleshooting under time-critical constraints. Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy software stacks and embedded systems in lab and field environments. Flight Data Capture & Analysis — Manage data collection during missions and post-test analysis, working with autonomy engineers to refine behaviors and identify improvements. Collaboration Across Teams — Work closely with autonomy, GNC, systems, and test teams to ensure mission-critical functionality is delivered on time and validated thoroughly. Continuous Improvement — Build tools and processes to improve integration timelines, flight test reliability, and team efficiency across deployment cycles. Support Certification and Compliance — Assist with documentation and system-level validation required for certification, airworthiness, and compliance in defense-relevant environments. Travel Requirement – Members of this team typically travel around 30-40% of the year (to different office locations, customer sites, and flight integration events). Required Qualifications: BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience. Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS). Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics. Knowledge of sensor integration, sensor fusion, and middleware frameworks (e.g., ROS, DDS). Hands-on experience supporting flight demos or live exercises. Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation. Strong problem-solving skills, with the ability to troubleshoot and optimize system performance. Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment. Ability to obtain a SECRET clearance. Preferred Qualifications: Direct experience supporting unmanned aerial systems or similar flight test campaigns. Familiarity with autonomy stacks, flight control systems, or GNC pipelines. Competence in sensor integration, electronics debugging, or avionics bring-up. Proficiency in developing automation tools for system testing, logging, and data parsing. Comfortable interfacing with DoD stakeholders during field events or technical reviews. Experience with UCI and OMS Standards. #LI-ED1 #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities. In this role, you'll develop and deploy advanced machine learning models that enable autonomous systems to better understand, reason about, and interact with their environment. You'll partner closely with machine learning researchers, autonomy engineers, perception engineers, and platform teams to translate emerging AI capabilities into reliable, production-ready systems for U.S. and international defense customers. This is an ideal opportunity for engineers who enjoy building state-of-the-art AI systems while solving the practical challenges of deploying them on operational autonomous platforms. What You'll Do: Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. Required Qualifications: Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience. Mastery of machine learning fundamentals. Experience training an deploying ML models for computer vision in a production setting. Strong understanding of 3D vision problems/algorithms. Experience with machine learning frameworks such as PyTorch and TensorFlow. Demonstrated expertise in deploying models using TensorRT and ONNX. Proficiency in C++ and Python. Strong analytical and problem-solving skills, with the ability to translate research into practical applications. Ability to obtain a SECRET clearance Preferred Qualifications: Experience with developing autonomous systems for defense customers. Experience with training/finetuning vision-language models, vision-language-action models, and/or world models. Contributions to open-source projects in machine learning or computer vision. Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA). #LI-DS-1 #LE Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities. In this role, you'll lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems. You'll own the team's most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy. Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you'll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization. What You'll Do: Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. Required Qualifications: Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience. Expertise of machine learning fundamentals. Experience training an deploying ML models for computer vision in a production setting. Strong understanding of 3D vision problems/algorithms. Experience with machine learning frameworks such as PyTorch and TensorFlow. Demonstrated expertise in deploying models using TensorRT and ONNX. Proficiency in C++ and Python. Strong analytical and problem-solving skills, with the ability to translate research into practical applications. Ability to obtain a SECRET clearance Preferred Qualifications: Experience with developing autonomous systems for defense customers. Experience with training/finetuning vision-language models, vision-language-action models, and/or world models. Contributions to open-source projects in machine learning or computer vision. Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA). #LI-DS-1 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Shield AI’s mission is to protect the lives of service members and civilians with intelligent systems. The Hardware Test Engineering team contributes to this effort by designing test solutions that drive high hardware reliability on our V-BAT vehicle. These solutions are in-house designed electrical and mechanical equipment used to perform component and system-level testing, both at ambient and in simulated harsh environmental conditions. In this role you will develop software that automates hardware testing, integrates test results with existing manufacturing software, create software infrastructure for scaling test automation to dozens of test stands, and create and manage databases for logging test results. Help us save lives as we strive to deliver the most highly reliable aerospace hardware in the industry. What you'll do: Architect, design, and develop software drivers and interfaces in Python for hardware systems, including PCBAs, avionics, sensors, and automated test equipment. Design and implement automated test frameworks to validate aircraft components and subsystems, ensuring scalability, reliability, and repeatability across multiple programs. Develop and evolve CI/CD pipelines that enable continuous integration, automated validation, and seamless deployment of test stand software. Build and maintain scalable test infrastructure and shared libraries, promoting modularity, reusability, and consistency across teams and platforms. Automate system provisioning and configuration management to accelerate deployment and maintenance of new test stands and test environments. Develop real-time monitoring and data visualization tools (e.g., Grafana) to deliver actionable insights during test execution and system debugging. Lead and participate in design and code reviews, championing sound architectural principles, testability, observability, and reliability throughout the software stack. Collaborate cross-functionally with hardware, systems, and QA teams to integrate software and test capabilities into broader aircraft validation workflows. Other duties as assigned. Required qualifications: B.S. in Computer Science, Computer Engineering, Electrical Engineering, or a related STEM field. Typically requires a minimum of 5 years of related experience Mastery of fundamental computer science topics. Advanced skillset for developing software in Python. Experience with Linux including Bash scripting and networking. Ability to configure and maintain small computer networks. Experience working on complex software development projects, which can be from an internship, job, club, team, personal project, etc… Demonstrated history of showing ownership of project outcomes and delivering exceptional results. Record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others. Preferred qualifications: Comfort working with hardware, as the testcases you write will interface with circuit boards, motors, and sensors. Mastery of fundamental engineering concepts including EE, Mech E, Programming, Physics, and Mathematics. Experience writing drivers for electronics test equipment. Demonstrated adaptability, agility, and the ability to innovate under pressure to meet dynamic project demands and drive successful outcomes. #LI-JM2 #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: The VBAT Software team is a motivated group of engineers focused on developing complex avionics software that merges hardware, operating systems and applications for cutting-edge Unmanned Aerial Vehicles (UAV). Embedded Software engineers work with customer programs, electrical engineers, Guidance, Navigation and Controls (GNC) engineers, systems engineers, test engineers and the autonomy team to design and develop software systems which utilize modern aerospace sensors, state-of-the-art UAV avionics, and groundbreaking Artificial Intelligence applications. As a member of the VBAT Software team, you will develop and maintain software architectures, generate and maintain all levels of software requirements, document and present software designs, coordinate software development, and marshal the entire suite of VBAT software through test and verification, release, and deployment to production and customers. What you'll do: Develop high-quality C/C++ code tailored specifically for V-Bat aircraft, ensuring optimal performance, reliability, and safety. Refine repository of existing firmware to support new hardware, features, and capabilities Integrate real-time operating system onto custom System-On-a-Module (SOM) Develop firmware to control robotic vehicles in flight Convert legacy bare-metal software to a RTOS based system Create new CI/CD pipelines with automated testing for embedded systems Participate in architecture, design, and code reviews Integrate software from multiple departments to include firmware, software test and verification, Autonomy AI, and Ground Control Stations (GCS) Develop software systems to implement and integrate interfaces to modern avionics sensors, sub-systems, and payloads Facilitate the design process for updates to the software system architecture Use modern software development tools and processes to capture our existing architecture and design future architectures Collaborating to define and extend systems engineering processes Report status, risks, accomplishments, expectations to senior leadership Work with the V-Bat production teams to manufacture UAVs in-house. Design and implement systems capable of conducting tests across various environments, including virtualized hardware and hardware-in-the-loop simulations, to facilitate thorough evaluation of software functionality and performance. Develop innovative tools to enhance the frequency and reliability of software deployment, test execution, and data analysis within a continuous integration and release system, fostering improved efficiency and productivity in software development workflows. Create prototypes to validate critical design concepts and assess technical limitations, providing tangible evidence of feasibility and informing decision-making processes. Required qualifications: Rock-solid software development experience in C/C++ Experience in bare-metal firmware development for embedded systems Linux Kernel or RTOS development - device trees and bring up on new hardware Familiarity with writing thread-safe multi-threaded programs Demonstrated track record of assuming ownership over development processes and features and delivering outstanding outcomes Proven track record of successfully shipping products, showcasing the ability to navigate through development cycles, overcome obstacles, and deliver high-quality solutions to meet project deadlines and exceed client expectations in a fast-paced environment Proactively identify opportunities for improvement within software development projects, demonstrating initiative to propose and implement innovative solutions that enhance efficiency, quality, and overall project success and V-Bat reliability B.S., M.S, PhD degree in Systems Engineering, Software Engineering, Computer Science or STEM (Science, Technology, Engineering, or Mathematics) discipline, such as Aerospace, Mechanical, or Electrical Engineering Preferred qualifications: Experience working on cutting-edge autonomous robotic systems including motor control Proven background in thriving within fast-paced environments, particularly within startup or R&D settings Demonstrated adaptability, agility, and the ability to innovate under pressure to meet dynamic project demands and drive successful outcomes. #LI-SM1 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.