Staff ML Infrastructure Engineer — Remote, Equity, Impact

Samsara; United States; Remote; USD 200,200 - 357,500; Full time

Benefits offered by this job

Flexible working model

Comprehensive health and parental leave plans

Professional development stipend

Job summary

A tech company specializing in IoT solutions is seeking a Staff/Senior Staff Machine Learning Infrastructure Engineer to design and evolve their ML platform. This remote position requires strong expertise in distributed computing frameworks like Ray and Spark, as well as hands-on experience with AWS and Kubernetes. The ideal candidate will lead technical initiatives, collaborate across teams, and drive improvements in real-world safety outcomes. An excellent opportunity for experienced professionals, offering competitive compensation and a flexible work model.

Qualifications

• 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 used by multiple teams.

Responsibilities

• Design and operate scalable online and batch inference systems.
• Collaborate on experiment design and evaluation.
• Lead throughput and cost estimation for new ML features.

Skills

Machine learning

Distributed computing frameworks

Cloud infrastructure (AWS)

Kubernetes

Production observability tooling

Education

10+ years in machine learning engineering or related fields

Tools

Ray

Spark

Job description

A tech company specializing in IoT solutions is seeking a Staff/Senior Staff Machine Learning Infrastructure Engineer to design and evolve their ML platform. This remote position requires strong expertise in distributed computing frameworks like Ray and Spark, as well as hands-on experience with AWS and Kubernetes. The ideal candidate will lead technical initiatives, collaborate across teams, and drive improvements in real-world safety outcomes. An excellent opportunity for experienced professionals, offering competitive compensation and a flexible work model.