About the role:

Samsara is the industry leader in AI for physical operations.

We’re hiring a Staff / Senior Staff Machine Learning Infrastructure Engineer to lead the design and evolution of our end-to-end ML platform powering Safety AI and adjacent product areas. This role combines deep platform ownership with direct product impact—enabling teams to build, deploy, and scale ML systems that improve real-world safety outcomes.

This is a remote position open to candidates based in the United States.

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
• You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together.

In this role, you will: 

ML Platform & Infrastructure

• Design, build, and operate Samsara’s end-to-end ML platform (training, experimentation, batch/online inference, edge) used by multiple Safety AI product teams.
• Evolve shared training and experimentation infrastructure (orchestration, clusters, environments) and standardize tracking, evaluation, and regression testing for fast, safe iteration.

Experimentation & Measurement

• Partner with product and applied ML teams to ship ML-powered features (CV models, EcoDriving insights, LLM-based reporting) that improve safety, reliability, and cost efficiency.
• Lead throughput and cost modeling for new ML features—from exploration to production-scale capacity planning—to inform roadmap and go/no-go decisions.
• Drive experiment design and evaluation, defining success metrics, structuring A/B or offline tests, and turning results into product and technical decisions.

Inference & Edge Deployment

• Design and operate scalable online and batch inference systems (Ray, Spark), including deployment patterns, observability, SLOs, and unified training-to-production workflows.
• Partner with firmware and edge teams to package, validate, and deploy models to Samsara devices, and build feedback loops from edge to cloud for continuous improvement.

Reliability, Security & Operations

• Own reliability, observability, and security for ML systems across cloud and edge, including on-call practices, incident response, and infrastructure hardening.
• Own or co-own end-to-end technical delivery for high-priority or high-risk initiatives, from modeling and system design through production rollout.

Leadership & Culture

• Provide Staff+/Senior-Staff technical leadership on ML infrastructure architecture and strategy, influencing cross-team decisions and mentoring engineers and applied scientists.
• Drive strong developer experience through documentation, office hours, and best practices, while contributing to and representing Samsara in open source communities (Ray, Spark, RayDP).
• Champion and role model Samsara’s cultural principles: Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team.

Minimum requirements for the role:

• 10+ years of overall experience in machine learning engineering or related fields, with a strong track record of building and operating large-scale ML systems.
• Strong experience with distributed computing frameworks such as Ray and/or Spark.
• Hands-on experience with cloud infrastructure (AWS), containers/Kubernetes, and production observability tooling.
• Proven experience building or supporting ML platforms (training, experimentation, or inference) used by multiple teams.
• Solid understanding of ML fundamentals including evaluation, experiment design, and model iteration in production environments.

An ideal candidate also has:

• Experience shipping ML-powered features end-to-end, from design through production and iteration, with measurable impact on product or business metrics.
• Background in computer vision and/or LLM-based systems in production environments.
• Experience with edge or on-device ML and collaboration with firmware or embedded teams.
• Familiarity with model lifecycle systems (model registry, deployment, monitoring, rollback, drift detection).
• Experience working in environments with strong security and compliance requirements.
• Demonstrated ability to lead across teams and influence technical direction at Staff+ scope.
• A strong sense of ownership and a desire for end-to-end autonomy—from platform design to real-world impact.

About the role:

The Safety AI team builds end-to-end computer vision and machine learning for Samsara’s AI dash cameras – delivering real-time driver safety insights and in-cab alerts. As a Sr. Manager of Machine Learning, you will lead teams that fuse on-device computer vision with IMU, GPS, and vehicle diagnostic data to detect, interpret, and surface actionable safety events and continuous risk signals. You’ll own the model lifecycle across edge and cloud – data curation, training, evaluation (including shadow/online experiments), deployment, monitoring, and iteration—and develop the core AI platform that powers these capabilities at fleet scale. You’ll partner closely with firmware, full-stack, and Platform teams to ship reliable, low-latency features, grounding detections in the “rules of the road” (e.g., stop signs and speed limits) to maximize precision and customer impact.

This is a remote position open to candidates residing in the United States. This position requires travel up to 5% of the time. Relocation assistance will not be provided for this role.

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
• You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together.

In this role, you will: 

• Lead teams of scientists and engineers working on CV, sensor fusion, and ML.
• Help architect, build, and improve solutions for hybrid cloud-edge ML.
• Actively contribute to building the roadmap for AI products at Samsara.
• Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.
• Hire, develop and lead an inclusive, engaged, and high performing team.

Minimum requirements for the role:

• BS or MS in Computer Science or other technical degree.
• 7+ years relevant technical experience with AI systems.
• 6+ years relevant software engineering work experience.
• 5+ years of experience leading large software and science teams including senior ICs.
• Experience building and deploying large-scale machine learning systems with feedback loops for continuous improvement.
• Comfortable leading full-stack / backend development in addition to science and research.

An ideal candidate also has:

• MS or PhD in Computer Science or other technical degree.
• Proven track record for innovation and delivering value to customers using AI.
• Customer orientation and intensive focus on improving the customer experience.
• Experience building, deploying, and optimizing AI systems than span edge devices and the cloud.
• Experience building products and solutions that rely on CV or sensor fusion.

About the role:

Samsara is the industry leader in AI for physical operations.

We’re hiring a Staff / Senior Staff Machine Learning Infrastructure Engineer to lead the design and evolution of our end-to-end ML platform powering Safety AI and adjacent product areas. This role combines deep platform ownership with direct product impact—enabling teams to build, deploy, and scale ML systems that improve real-world safety outcomes.

This is a remote position open to candidates based in Canada.

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
• You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together.

In this role, you will: 

ML Platform & Infrastructure

• Design, build, and operate Samsara’s end-to-end ML platform (training, experimentation, batch/online inference, edge) used by multiple Safety AI product teams.
• Evolve shared training and experimentation infrastructure (orchestration, clusters, environments) and standardize tracking, evaluation, and regression testing for fast, safe iteration.

Experimentation & Measurement

• Partner with product and applied ML teams to ship ML-powered features (CV models, EcoDriving insights, LLM-based reporting) that improve safety, reliability, and cost efficiency.
• Lead throughput and cost modeling for new ML features—from exploration to production-scale capacity planning—to inform roadmap and go/no-go decisions.
• Drive experiment design and evaluation, defining success metrics, structuring A/B or offline tests, and turning results into product and technical decisions.

Inference & Edge Deployment

• Design and operate scalable online and batch inference systems (Ray, Spark), including deployment patterns, observability, SLOs, and unified training-to-production workflows.
• Partner with firmware and edge teams to package, validate, and deploy models to Samsara devices, and build feedback loops from edge to cloud for continuous improvement.

Reliability, Security & Operations

• Own reliability, observability, and security for ML systems across cloud and edge, including on-call practices, incident response, and infrastructure hardening.
• Own or co-own end-to-end technical delivery for high-priority or high-risk initiatives, from modeling and system design through production rollout.

Leadership & Culture

• Provide Staff+/Senior-Staff technical leadership on ML infrastructure architecture and strategy, influencing cross-team decisions and mentoring engineers and applied scientists.
• Drive strong developer experience through documentation, office hours, and best practices, while contributing to and representing Samsara in open source communities (Ray, Spark, RayDP).
• Champion and role model Samsara’s cultural principles: Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team.

Minimum requirements for the role:

• 10+ years of overall experience in machine learning engineering or related fields, with a strong track record of building and operating large-scale ML systems.
• Strong experience with distributed computing frameworks such as Ray and/or Spark.
• Hands-on experience with cloud infrastructure (AWS), containers/Kubernetes, and production observability tooling.
• Proven experience building or supporting ML platforms (training, experimentation, or inference) used by multiple teams.
• Solid understanding of ML fundamentals including evaluation, experiment design, and model iteration in production environments.

An ideal candidate also has:

• Experience shipping ML-powered features end-to-end, from design through production and iteration, with measurable impact on product or business metrics.
• Background in computer vision and/or LLM-based systems in production environments.
• Experience with edge or on-device ML and collaboration with firmware or embedded teams.
• Familiarity with model lifecycle systems (model registry, deployment, monitoring, rollback, drift detection).
• Experience working in environments with strong security and compliance requirements.
• Demonstrated ability to lead across teams and influence technical direction at Staff+ scope.
• A strong sense of ownership and a desire for end-to-end autonomy—from platform design to real-world impact.

About the role:

The Safety AI team builds end-to-end computer vision and machine learning for Samsara’s AI dash cameras – delivering real-time driver safety insights and in-cab alerts. As a Sr. Manager of Machine Learning, you will lead teams that fuse on-device computer vision with IMU, GPS, and vehicle diagnostic data to detect, interpret, and surface actionable safety events and continuous risk signals. You’ll own the model lifecycle across edge and cloud – data curation, training, evaluation (including shadow/online experiments), deployment, monitoring, and iteration—and develop the core AI platform that powers these capabilities at fleet scale. You’ll partner closely with firmware, full-stack, and Platform teams to ship reliable, low-latency features, grounding detections in the “rules of the road” (e.g., stop signs and speed limits) to maximize precision and customer impact.

This is a remote position open to candidates residing in Canada. This position requires travel up to 5% of the time. Relocation assistance will not be provided for this role.

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
• You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together.

In this role, you will: 

• Lead teams of scientists and engineers working on CV, sensor fusion, and ML.
• Help architect, build, and improve solutions for hybrid cloud-edge ML.
• Actively contribute to building the roadmap for AI products at Samsara.
• Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.
• Hire, develop and lead an inclusive, engaged, and high performing team.

Minimum requirements for the role:

• BS or MS in Computer Science or other technical degree.
• 7+ years relevant technical experience with AI systems.
• 6+ years relevant software engineering work experience.
• 5+ years of experience leading large software and science teams including senior ICs.
• Experience building and deploying large-scale machine learning systems with feedback loops for continuous improvement.
• Comfortable leading full-stack / backend development in addition to science and research.

An ideal candidate also has:

• MS or PhD in Computer Science or other technical degree.
• Proven track record for innovation and delivering value to customers using AI.
• Customer orientation and intensive focus on improving the customer experience.
• Experience building, deploying, and optimizing AI systems than span edge devices and the cloud.
• Experience building products and solutions that rely on CV or sensor fusion.