Remote Senior ML Engineer, Safety AI Backend

Samsara; Los Angeles (CA); Remote; USD 170,000 - 286,000; Full time

Benefits offered by this job

RSU grant

Remote-friendly model

Professional development stipend

Parental leave

Job summary

Samsara is seeking a Senior ML Engineer to own the cloud-side path from model artifacts to production systems for Safety AI. You will design low-latency ML APIs and build scalable data pipelines that power continuous model iteration and safe deployments, collaborating closely with scientists and engineers to ensure robust, cost-efficient production workflows.

The role emphasizes production-quality systems and end-to-end lifecycle management, from artifact to rollout monitoring, with

Qualifications

• 6+ years of experience as a Machine Learning Engineer or similar role, shipping models in production.
• Proficiency in one or more common languages (C++, Golang, Java, Python, Scala).
• Experience deploying models with real customer feedback loops.
• Comfort with full-stack/backend development and understanding data structures underneath your models.
• BS or MS in Computer Science or related field.

Responsibilities

• Design Production ML APIs to integrate model outputs into cloud apps.
• Build scalable data flywheels for continuous model iteration, backtesting, and evaluation.
• Optimize and serve artifacts handed off by scientists for production workloads.
• Process petabyte-scale camera and sensor data to support model execution and dataset curation.
• Monitor rollout health, drift, precision/recall, and latency in production.

Skills

C++

Golang

Java

Python

Scala

ML tooling

Model deployment

Full-stack/backend

Education

BS or MS in Computer Science or related field

PhD in CS or quantitative discipline (nice to have)

Tools

Docker

Kubernetes

Ray/Ray Serve

MLflow

Grafana

PyTorch

Spark

Job description

Samsara is seeking a Senior ML Engineer to own the cloud-side path from model artifacts to production systems for Safety AI. You will design low-latency ML APIs and build scalable data pipelines that power continuous model iteration and safe deployments, collaborating closely with scientists and engineers to ensure robust, cost-efficient production workflows.

The role emphasizes production-quality systems and end-to-end lifecycle management, from artifact to rollout monitoring, with