Senior Machine Learning Engineer

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Take ownership of the cloud-side journey from model artifact to production system for Safety AI ML applications.

• Set standards for serving, evaluating, versioning, and monitoring production models.

• Develop reliable, low-latency ML APIs tailored for cloud applications.

• Create scalable data pipelines for model iteration, backtesting, shadow evaluation, and online assessment.

• Productionize model artifacts and enhance serving logic for platform-specific workloads.

• Process large volumes of camera and sensor telematics data for model execution, backtesting, and dataset curation.

• Monitor model drift, precision/recall, latency regressions, rollout health, and feedback loops.

• Collaborate with firmware and platform teams to optimize edge-to-cloud model execution.

• Partner with product managers to convert safety requirements into scalable technical architectures.

• Work alongside applied scientists, firmware engineers, full-stack engineers, and product managers.

• Advocate for and integrate Samsara’s cultural principles as the organization grows.

⛳️ Requirements

• Over 6 years of experience as a Machine Learning Engineer or a similar position, with a proven history of deploying models in production.

• Strong expertise in one or more popular programming languages, such as C++, Golang, Java, Python, or Scala.

• Proficient in ML tools including Ray/Ray Serve, MLflow, Grafana, PyTorch, and Spark.

• Experience in deploying and iteratively refining models using real customer feedback loops.

• Comfortable with full-stack/backend development and possess an understanding of data structures and model dependencies.

• Bachelor’s or Master’s degree in Computer Science or a related quantitative discipline.

• Familiarity with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code frameworks.

• Experience in deploying and managing ML applications in AWS, GCP, or Azure cloud environments.

• Proven track record of shipping end-to-end ML applications, particularly in safety-critical or high-scale sectors.

• Expertise in optimizing distributed model training using GPUs.

• A Ph.D. in Computer Science or a quantitative discipline is preferred for ideal candidates.

🏝️ Benefits

• Initial RSU grant without a vesting cliff.

• Ongoing refresh opportunities linked to performance.

• Performance-based bonuses or variable pay.

• Equity options for eligible positions.

• Flexible, employee-driven remote working model.

• Professional development stipend available.

• Comprehensive health care plans.

• Parental leave options.

• Flexible working arrangements.

• Support for remote work.