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At MNTN, we put our people first, full stop. This allows our company culture to be defined by our team members and their shared values, like trust, ambition, quality, radical honesty, and compassionate leadership. It’s why we all really love working for the Hardest Working Software in Television™ (and also why we were named one of Ad Age’s Best Places To Work in 2026.) We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising. Our self-serve technology makes running TV ads as easy as search and social, helping brands drive measurable conversions, revenue, site visits, and more. It’s what led MNTN to being named one of Fast Company's Most Innovative Companies in 2023. You can learn more about us and everything we do by visiting https://mountain.com/ . We’re committed to innovation that empowers, not replaces. At MNTN, AI is a tool for growth, enhancing efficiency while keeping a people-first approach. Our goal is to streamline workflows and drive new solutions—without compromising the human element that makes our company great. So if wanting to do more, own more, and make a bigger impact comes naturally to you, then you may be the person we're looking for to join us in our next stage of growth. This is a senior, hands-on security engineering role focused on continuously improving the security posture of the MNTN platform through architecture, automation, and platform engineering. You'll work as a technical peer across DevOps and Engineering, with scope spanning application, cloud, Kubernetes, systems, and network architecture. You'll combine hands-on work with individual teams and internal consulting to shape secure designs, solve complex problems, and turn recurring risks and requirements into secure defaults, reusable controls, self-service platform capabilities, and automated security observability. The goal is to make strong security practices consistent, measurable, and easy to adopt across Engineering. This is not a GRC or audit role. Your impact comes from deep technical judgment, effective collaboration, and making good security decisions repeatable across the organization. What you’ll do Shape security architecture across applications, cloud infrastructure, Kubernetes, networking, CI/CD, identity, and data flows. Partner with engineering teams on architecture and threat modeling, helping design secure systems before they ship. Turn security requirements and recurring risks into secure defaults, reusable platform capabilities, policy-as-code, and automated enforcement. Build automated security monitoring and response, including CVE detection, prioritization, remediation, verification, alerting, and visibility into control failures. Design and operate secure infrastructure primarily on **Google Cloud and GKE**, using Kubernetes as the core platform abstraction. Implement and evolve controls for IAM/RBAC, workload identity, least privilege, secrets, environment isolation, network segmentation, container security, and software supply chain. Build automation, infrastructure tooling, and CI/CD systems using GitOps, Terraform / OpenTofu, Crossplane, Argo, APIs, SDKs, and code. What success looks like Security is addressed through architecture and platform design, not one-off fixes. Secure defaults and self-service capabilities make strong security practices easy to adopt. Security risks and control failures are visible through automated monitoring and actionable alerting. Reusable controls and standards improve security consistently across teams and systems. Engineering teams trust you as an expert technical peer and involve you early in important design decisions. What you’ll bring 5+ years in Platform, DevOps, SRE, Infrastructure, Cloud Security, or related engineering roles, with meaningful production ownership. Deep security engineering knowledge across application, cloud, Kubernetes, identity, networking, data, and software supply chain. Deep cloud and Kubernetes experience; **GCP/GKE strongly preferred**, with equivalent major-cloud experience considered. Strong understanding of application and systems architecture, APIs, authentication/authorization, distributed systems, networking, and trust boundaries. Strong software engineering and automation skills in Python and Typescript, including APIs, SDKs, CLIs, and internal tooling. Deep Terraform / OpenTofu and Kubernetes experience, including reusable infrastructure patterns, GitOps, Helm, ArgoCD, RBAC, and workload security. Experience with threat modeling, security observability, and translating security or compliance requirements into practical technical controls. A platform mindset: you solve recurring problems with abstractions, paved roads, automation, and self-service rather than manual processes. Comfortable using AI-assisted engineering tools daily while independently validating correctness, security, and operational impact. Able to operate independently, consult effectively with engineering teams, communicate architectural tradeoffs, and influence senior technical peers. About MNTN Our recruiters will always reach out using an email address ending with @mountain.com OR @mntn.com. If you’re contacted by someone without that address and they mention a Reference Code (which we never use), then that ain’t us folks. Tell those trolls to take a hike–you’re waiting to climb a MNTN. MNTN provides advertising software for brands to reach their audience across Connected TV, web, and mobile. MNTN Performance TV has redefined what it means to advertise on television, transforming Connected TV into a direct-response, performance marketing channel. Our web retargeting has been leveraged by thousands of top brands for over a decade, driving billions of dollars in revenue. Our solutions give advertisers total transparency and complete control over their campaigns all with the fastest go-live in the industry. As a result, thousands of top brands have partnered with MNTN, including Tarte, Decked, and National University. #LI-Remote

At MNTN, we put our people first, full stop. This allows our company culture to be defined by our team members and their shared values, like trust, ambition, quality, radical honesty, and compassionate leadership. It’s why we all really love working for the Hardest Working Software in Television™ (and also why we were named one of Ad Age’s Best Places To Work in 2026.) We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising. Our self-serve technology makes running TV ads as easy as search and social, helping brands drive measurable conversions, revenue, site visits, and more. It’s what led MNTN to being named one of Fast Company's Most Innovative Companies in 2023. You can learn more about us and everything we do by visiting https://mountain.com/ . We’re committed to innovation that empowers, not replaces. At MNTN, AI is a tool for growth, enhancing efficiency while keeping a people-first approach. Our goal is to streamline workflows and drive new solutions—without compromising the human element that makes our company great. So if wanting to do more, own more, and make a bigger impact comes naturally to you, then you may be the person we're looking for to join us in our next stage of growth. The MNTN Media Buying Intelligence team helps brands reach the right customers with software that turns petabytes of data into meaningful campaign strategies. Our engineers, data scientists and analysts build software that serves content to millions of people every day. As a Senior Machine Learning Engineer, you will focus on operationalizing machine learning models by taking ownership of prototypes built by data scientists and turning them into robust, scalable production systems. You will lead the deployment, monitoring, and maintenance of ML solutions that power campaign optimizations at scale. This role emphasizes strong software engineering practices, designing for reliability and performance, and working with large-scale data pipelines and infrastructure. You’ll collaborate across functions to ensure models are not just accurate but production-ready, scalable, and cost-effective. This is a senior machine learning role with an emphasis on building production-ready models. It is not a pure research role. You are expected to ship production-grade implementations and own outcomes in production. What You’ll Do: Design and build a robust marketing platform that reaches the right audience, anywhere and anytime Build high-volume services that remain reliable at scale Develop big data solutions using open-source frameworks Design, train, evaluate, and improve models for deliverability, forecasting, and optimization Improve model quality by refining thresholds, calibration, and guardrails to reduce false positives and decision noise Build offline and online evaluation workflows tied to measurable business outcomes, enabling faster testing and more confident releases Partner with Product, Project Leads, and platform-focused Machine Learning and Data Engineers to improve service reliability, latency, observability, and data freshness Share ownership of production systems, including shipping model improvements safely and participating in the on-call rotation What Success Looks Like: Model quality improves on agreed business and operational metrics. False positives,unstable decision behavior, and other secondary metrics are reduced in key flow. Model testing/evaluation cycles become materially faster, better, and more performant. More product testing and analysis More model improvements reach production safely and predictably. What You’ll Bring: 5+ years building ML models that were deployed and operated in production. Extreme Proficiency in technical communication to nontechnical stakeholders. Excellent applied ML fundamentals (classification/regression/forecasting + evaluation rigor) Strong optimization understanding in business context Strong Python and SQL with production engineering discipline (testing, maintainability, performance). Experience balancing model quality, system constraints, and speed-to-production. Strong experience with ownership and cross-functional collaboration. Experience in ad tech, growth analytics, personalization, or performance marketing Proficiency working with real-time or near-real-time data pipelines Experience with experimentation frameworks and production model monitoring. Experience large scale data processing and ML systems such as: Kedro, AutoGluon, PyTorch, Polars, BigQuery/GCP, Airflow/SQLMesh, and Databricks ecosystems. Experience in Reinforcement Learning such as Q-Learning or Multi-Armed Bandits is a plus. About MNTN Our recruiters will always reach out using an email address ending with @mountain.com OR @mntn.com. If you’re contacted by someone without that address and they mention a Reference Code (which we never use), then that ain’t us folks. Tell those trolls to take a hike–you’re waiting to climb a MNTN. MNTN provides advertising software for brands to reach their audience across Connected TV, web, and mobile. MNTN Performance TV has redefined what it means to advertise on television, transforming Connected TV into a direct-response, performance marketing channel. Our web retargeting has been leveraged by thousands of top brands for over a decade, driving billions of dollars in revenue. Our solutions give advertisers total transparency and complete control over their campaigns all with the fastest go-live in the industry. As a result, thousands of top brands have partnered with MNTN, including Tarte, Decked, and National University. #LI-Remote

At MNTN, we put our people first, full stop. This allows our company culture to be defined by our team members and their shared values, like trust, ambition, quality, radical honesty, and compassionate leadership. It’s why we all really love working for the Hardest Working Software in Television™ (and also why we were named one of Ad Age’s Best Places To Work in 2026.) We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising. Our self-serve technology makes running TV ads as easy as search and social, helping brands drive measurable conversions, revenue, site visits, and more. It’s what led MNTN to being named one of Fast Company's Most Innovative Companies in 2023. You can learn more about us and everything we do by visiting https://mountain.com/ . We’re committed to innovation that empowers, not replaces. At MNTN, AI is a tool for growth, enhancing efficiency while keeping a people-first approach. Our goal is to streamline workflows and drive new solutions—without compromising the human element that makes our company great. So if wanting to do more, own more, and make a bigger impact comes naturally to you, then you may be the person we're looking for to join us in our next stage of growth. The MNTN Targeting Group helps brands reach the right customers with software that turns petabytes of data into meaningful audience targeting strategies. Our engineers, data scientists and analysts build software that serves content to millions of people every day. You'll be joining the team working on MNTN Matched, our flagship machine learning product that is a critical revenue driver for the business. As a Senior Backend Engineer, you’ll be deeply involved in developing and improving the core models and systems that power our targeting products. Your work will directly influence the quality, efficiency, and innovation of our targeting platform. What You’ll Do: Create and support Kotlin APIs and services to support our targeting distributed systems - the most critical component in our business Work in many environments, including languages and tools like Rust, PySpark, Kafka, and several RDBMSes Understand the broader context of our software beyond the components you build Raise the bar on our engineering culture, leading by example Build high volume services that are reliable at scale Work with enormous volumes of data (100s of TB daily) Collaborate with and explain complex technical issues to Product and Project Leads Optimize and enhance existing products What You’ll Bring: 5+ years of Java, Kotlin, or Scala development experience Comfort diving in to tech stacks outside your primary specialization A desire to understand the purpose and impact of the tools you build Strong proficiency in SQL, table design, indexing and other common database skills Integration of AI tools such as Cursor, ChatGPT and other LLM based copilots in your workflow Experience with Microservice style architecture Familiarity with Git and Linux/UNIX environments Experience on AWS, GCP, or other cloud infrastructure About MNTN Our recruiters will always reach out using an email address ending with @mountain.com OR @mntn.com. If you’re contacted by someone without that address and they mention a Reference Code (which we never use), then that ain’t us folks. Tell those trolls to take a hike–you’re waiting to climb a MNTN. MNTN provides advertising software for brands to reach their audience across Connected TV, web, and mobile. MNTN Performance TV has redefined what it means to advertise on television, transforming Connected TV into a direct-response, performance marketing channel. Our web retargeting has been leveraged by thousands of top brands for over a decade, driving billions of dollars in revenue. Our solutions give advertisers total transparency and complete control over their campaigns all with the fastest go-live in the industry. As a result, thousands of top brands have partnered with MNTN, including Tarte, Decked, and National University. #LI-Remote