Remote Senior ML Engineer, Safety AI Backend

Samsara; Washington (District of Columbia); Remote; USD 170,000 - 286,000; Full time

Job summary

Samsara is seeking a senior ML Engineer to own cloud-side production ML APIs and data pipelines for Safety AI. You will design, deploy, and monitor scalable ML systems that serve millions of edge devices and cloud workloads, partnering with scientists and engineers to translate research into robust, cost-efficient production solutions.

With 6+ years in ML, you will optimize models for low latency and high throughput while ensuring safety-critical performance.

Qualifications

• 6+ years of experience as a Machine Learning Engineer or similar role.
• Strong proficiency in one or more languages (C++, Golang, Java, Python, Scala).
• Proficiency with ML tools (e.g. Ray/Ray Serve, MLflow, Grafana, PyTorch, Spark).
• Experience deploying and iteratively refining models using real customer feedback loops.
• BS or MS in Computer Science or a related quantitative field.

Responsibilities

• Design Production ML APIs to integrate model outputs directly into cloud applications.
• Build scalable data flywheels powering continuous model iteration, backtesting, shadow and online evaluation.
• Productionize model artifacts and optimize serving for platform workloads.
• Process petabyte-scale camera and sensor data to support model execution and dataset curation.
• Monitor drift, precision/recall, and latency regressions in production to ensure safe rollout.
• Collaborate with firmware and platform teams to optimize edge-to-cloud model execution.
• Translate safety requirements into scalable technical architectures with product teams.

Skills

C++

Golang

Java

Python

Scala

Education

BS or MS in Computer Science or related quantitative field

PhD in Computer Science or quantitative discipline

Tools

Ray/Ray Serve

MLflow

Grafana

PyTorch

Spark

Job description

Samsara is seeking a senior ML Engineer to own cloud-side production ML APIs and data pipelines for Safety AI. You will design, deploy, and monitor scalable ML systems that serve millions of edge devices and cloud workloads, partnering with scientists and engineers to translate research into robust, cost-efficient production solutions.

With 6+ years in ML, you will optimize models for low latency and high throughput while ensuring safety-critical performance.