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Scaleai
Actively Hiring139 open positions matching criteria
Machine Learning Engineer, Platform
Applications Platform Engineering
Machine Learning Engineer London, UK About the role Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities. This role owns the context and memory capabilities within AIS, including their correctness, performance, and evaluation. We are looking for a Machine Learning Engineer who can own hard technical problems end to end — from research and prototyping through to production deployment — working across knowledge bases, vector stores, RAG pipelines, and context engines to power agents that deliver real impact for enterprise customers. What you'll do Own large areas of the platform end to end, from design through to production deployment. Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data. Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking. Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services. Develop context retrieval systems that balance recall, precision, latency, and cost. Build evaluation frameworks, datasets, and metrics to measure retrieval quality, context relevance, and end to end agent performance. Build reliable backend services and data pipelines that support ML and LLM components in production. Deliver experiments and new capabilities quickly, maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of the platform. What we look for 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases. Strong engineering fundamentals, supported by a Master’s or PhD degree in Computer Science, Machine Learning, AI, or equivalent practical experience.. A deep, hands-on understanding of retrieval systems, RAG, embeddings, vector indexing, knowledge representation, and semantic search. Proven proficiency in Python, including writing production-quality, testable, and maintainable code. The ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints. Strong communication skills and comfort working in customer-facing or cross-functional environments. Experience scaling products at hyper growth startups PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Machine Learning Engineer, Public Sector
Public Sector Engineering
The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. You will: Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines Work with massive datasets to develop both generic models as well as fine tune models for specific products Build scalable machine learning infrastructure to automate and optimize our ML services Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You’d Have: 2+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in Tensorflow or PyTorch Nice to Haves: Experience deploying software into environments you can't reach from your laptop - on-prem, edge, air-gapped, or otherwise restricted networks. Regulated industries count; the constraint is the point, not the sector. Any prior exposure to government or defense work: military or civilian service, a cleared internship, or time at a federal contractor. Hands-on fine-tuning of open-weight models - LoRA/PEFT, instruction tuning, or training embedding models, at work or on your own. Having written evaluations for a system whose output isn't deterministic: benchmarks, LLM judges, or a regression suite that caught something real. Experience with geospatial data or maps - GIS tooling, spatial reference systems, or imagery. A shipped project with real users behind it, where you owned it after launch rather than handing it off at merge. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of Washington DC is: $235,200 — $294,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Machine Learning Engineer, Public Sector
Public Sector Engineering
The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. You will: Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines Work with massive datasets to develop both generic models as well as fine tune models for specific products Build scalable machine learning infrastructure to automate and optimize our ML services Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You’d Have: 2+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in Tensorflow or PyTorch Nice to Haves: Experience deploying software into environments you can't reach from your laptop - on-prem, edge, air-gapped, or otherwise restricted networks. Regulated industries count; the constraint is the point, not the sector. Any prior exposure to government or defense work: military or civilian service, a cleared internship, or time at a federal contractor. Hands-on fine-tuning of open-weight models - LoRA/PEFT, instruction tuning, or training embedding models, at work or on your own. Having written evaluations for a system whose output isn't deterministic: benchmarks, LLM judges, or a regression suite that caught something real. Experience with geospatial data or maps - GIS tooling, spatial reference systems, or imagery. A shipped project with real users behind it, where you owned it after launch rather than handing it off at merge. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of Washington DC is: $235,200 — $294,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Machine Learning Engineer, Public Sector
Public Sector Engineering
The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. You will: Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines Work with massive datasets to develop both generic models as well as fine tune models for specific products Build scalable machine learning infrastructure to automate and optimize our ML services Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment Comfortable with light travel (approximately 10%) for customer interaction and team needs This role will require an active TS security clearance Ideally You’d Have: 2+ years of experience building and deploying applied ML systems in production environments Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment Solid background in algorithms, data structures, and object-oriented programming Strong programming skills in Python, experience in Tensorflow or PyTorch Nice to Haves: Experience deploying software into environments you can't reach from your laptop - on-prem, edge, air-gapped, or otherwise restricted networks. Regulated industries count; the constraint is the point, not the sector. Any prior exposure to government or defense work: military or civilian service, a cleared internship, or time at a federal contractor. Hands-on fine-tuning of open-weight models - LoRA/PEFT, instruction tuning, or training embedding models, at work or on your own. Having written evaluations for a system whose output isn't deterministic: benchmarks, LLM judges, or a regression suite that caught something real. Experience with geospatial data or maps - GIS tooling, spatial reference systems, or imagery. A shipped project with real users behind it, where you owned it after launch rather than handing it off at merge. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of Washington DC is: $235,200 — $294,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Machine Learning Fellow - Human Frontier Collective (Canada)
Human Frontier Collective
About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus. Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration. How it works Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement. Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the country they reside in. Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more. Projects Logistics : Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more. Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves. Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications. Application process Apply: We review applications on a rolling basis. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Note: If we invited you directly, your invitation will say whether this step applies. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. ------ PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Machine Learning Fellow - Human Frontier Collective (UK)
Human Frontier Collective
About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus. Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration. How it works Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement. Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the country they reside in. Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more. Projects Logistics : Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more. Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves. Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications. Application process Apply: We review applications on a rolling basis. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Note: If we invited you directly, your invitation will say whether this step applies. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. ------ PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Machine Learning Fellow - Human Frontier Collective (US)
Human Frontier Collective
About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus. Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration. How it works Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement. Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the US. Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more. Projects Logistics : Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more. Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves. Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications. Application process Apply: We review applications on a rolling basis. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Note: If we invited you directly, your invitation will say whether this step applies. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. ------ PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
View more...Applied AI Engineer, Global Public Sector
GPS Engineering
Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI We are hiring Applied AI Engineers to build custom end-to-end AI applications for our public sector clients using the latest developments in the field of AI. You will also get the opportunity to develop and be part of creating custom datasets, evaluations, and fine-tuning these sophisticated models to maximize performance and apply on real world use cases with global reach. At Scale, we’re not just building AI solutions—we are building repeatable blocks to enable the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a member of our rapidly expanding team, we’d love to hear from you. You will: Partner with public sector clients to deeply understand their challenges and define AI-driven solutions Build and deploy end-to-end AI applications into production leveraging latest developments from the biggest AI labs, and open source models Collaborate with cross-functional teams, including data annotation specialists, to create high-quality training datasets Design and maintain robust evaluation frameworks to ensure the reliability and effectiveness of AI models Participate in customer engagements, including occasional travel (approximately two weeks per quarter) Contribute to the scaling of AI capabilities in the public sector through hands-on knowledge sharing Ideally you’d have: A strong engineering background, with a Bachelor’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience) 7+ years of post-graduation engineering experience, with demonstrated proficiency in languages such as Python, TypeScript/JavaScript, Java, or C++. 2+ years of experience applying AI/ML in production environments, such as deploying deep learning solutions, building generative/agentic AI applications or setting up evaluations pipelines Familiarity with cloud-based machine learning tools and platforms (e.g. AWS, GCP, Azure) Strong problem-solving skills, with a data-driven approach to iterating on machine learning models and datasets Excellent written and verbal communication skills to collaborate effectively in a cross-functional environment Nice to haves: Experience working at a startup, particularly as founding engineer Experience building and deploying large-scale AI solutions Strong written and verbal communication skills to operate in a cross-functional team environment Proficiency in Arabic (if focused on language models) For those applying based in Qatar: Residency and employment in Qatar requires certain permissions (visa and permits) issued by the Qatari authorities. As part of the application process, candidates will be asked to provide personal information, including residency status and nationality, which is required for visa processing. This information is collected solely for immigration compliance purposes and will be not used as a criterion in any hiring decision unless such use is lawfully permitted. Visa issuance is at the discretion of the Qatari authorities. If you are successful in your application, you will be required to provide the documentation requested by Scale and the authorities to obtain the necessary permissions for you to live and work in Qatar, and Scale will work with successful candidates to support the visa application process. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
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