Senior Machine Learning Engineer
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Job Description
Senior Machine Learning Engineer productionizing computer vision models for Samsara’s IoT-powered Connected Operations Cloud. Building low-latency APIs, data pipelines, and monitoring for fleet-scale safety features.
Responsibilities:
- Own the cloud-side path from model artifact to production system for Safety AI ML applications
- Establish standards for serving, evaluating, versioning, and monitoring production models
- Build reliable, low-latency ML APIs for cloud applications
- Construct scalable data pipelines for model iteration, backtesting, shadow evaluation, and online evaluation
- Productionize model artifacts and optimize serving logic for platform-specific workloads
- Process high-volume camera and sensor telematics data for model execution, backtesting, and dataset curation
- Monitor model drift, precision/recall, latency regressions, rollout health, and feedback loops
- Partner with firmware and platform teams to optimize edge-to-cloud model execution
- Work with product managers to translate safety requirements into scalable technical architectures
- Collaborate with applied scientists, firmware engineers, full-stack engineers, and product managers
- Champion and embed Samsara’s cultural principles as the company scales
Requirements:
- 6+ years of experience as a Machine Learning Engineer or similar role, with a track record of shipping models in production
- Strong proficiency in one or more common languages, such as C++, Golang, Java, Python, or Scala
- Proficiency with ML tools such as Ray/Ray Serve, MLflow, Grafana, PyTorch, and Spark
- Experience deploying and iteratively refining models using real customer feedback loops
- Comfort with full-stack/backend development and understanding of data structures and model dependencies
- BS or MS in Computer Science or a related quantitative field
- Experience with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code frameworks
- Experience deploying and managing ML applications in AWS, GCP, or Azure cloud environments
- Experience shipping end-to-end ML applications, ideally in safety-critical or high-scale domains
- Expertise optimizing distributed model training with GPUs
- Ph.D. in Computer Science or a quantitative discipline is an ideal-candidate qualification
Benefits:
- Initial RSU grant with no vesting cliff
- Ongoing refresh opportunities tied to performance
- Performance-based bonus/variable pay
- Equity for eligible roles
- Flexible, employee-led remote model
- Professional development stipend
- Comprehensive health plans
- Parental leave plans
- Flexible working model
- Remote work support
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