Design, build, and operate Samsara’s end-to-end ML platform spanning training, experimentation, batch and online inference, and edge deployment
Partner with product and applied ML teams to design, launch, and iterate ML-powered features driving measurable improvements in safety outcomes, feature reliability, and cost efficiency
Lead throughput and cost estimation for new ML features, informing roadmap and go/no-go decisions
Collaborate on experiment design and evaluation
Evolve shared training and experimentation infrastructure and standardize experiment tracking, evaluation, and regression testing
Design and operate scalable online and batch inference systems, including deployment patterns, observability, and SLOs
Partner with firmware and edge teams to define workflows for packaging, validating, and deploying models
Own the reliability, observability, and security posture of ML systems
Provide Staff+/Senior-Staff-level technical leadership
Drive strong developer experience through documentation and best practices
Own or co-own end-to-end technical delivery for high-priority initiatives.

Requirements

10+ years of overall experience in machine learning engineering or related fields
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.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learning engineeringdistributed computing frameworksRaySparkcloud infrastructureAWScontainersKubernetesML platformsexperiment design

Soft Skills

technical leadershipcollaborationdocumentationbest practicescommunication