Note: The job is a remote job and is open to candidates in USA. Samsara is a provider of the Connected Operations Cloud, helping organizations that depend on physical operations improve safety, efficiency, and sustainability through IoT data. The Senior Machine Learning Engineer will build resilient, low-latency ML backend systems for Safety AI, including production APIs, data pipelines, model-serving infrastructure, and evaluation and monitoring systems. The role partners with applied scientists, firmware and platform engineers, and product managers to deploy scalable, reliable safety features.
Responsibilities
- Own the cloud-side path from model artifact to production system for Safety AI's ML applications
- Establish practical standards for productionizing models — how they're served, evaluated, versioned, and monitored once they leave applied science
- Set a high bar for reliability: rigorous evaluation, measurable rollout health, and systems that degrade predictably rather than silently
- Act as a technical partner to applied scientists, helping translate research outputs into systems that are debuggable, scalable, and cost-efficient in production
- Design Production ML APIs: Architect and maintain reliable, low-latency APIs to integrate Safety AI model outputs directly into cloud applications
- Build Data Flywheels: Construct scalable pipelines to power continuous model iteration, backtesting, shadow and online evaluation, enabling fast and safe deployments
- Optimize & Serve Artifacts: Productionize model artifacts handed off by applied scientists, optimizing serving logic and fine-tuning models for platform-specific workloads
- Petabyte-Scale Operations: Process high-volume camera and sensor telematics data to support model execution, backtesting, and automated dataset curation
- Monitor & Maintain Rollout Health: Build systems to track model drift, precision/recall, and latency regressions in production, ensuring predictable failure modes and closed-loop data feedback
- Cross-Functional System Integration: Partner with firmware and platform teams to optimize edge-to-cloud model execution, balancing latency, throughput, and infrastructure cost
- Product Collaboration: Work with product managers to translate safety requirements into scalable technical architectures
- Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices
Skills
- This is a remote role open to candidates residing in the US or Canada
- 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 (e.g., C++, Golang, Java, Python, Scala)
- Proficiency with common ML tools (e.g. Ray/Ray Serve, MLflow, Grafana, Pytorch, Spark, etc)
- Experience deploying and iteratively refining models using real customer feedback loops
- Comfort with full-stack/backend development — you understand the data structures and dependencies underneath your models
- BS or MS in Computer Science or a related quantitative field
- Ph.D. in Computer Science or a quantitative discipline (e.g., Applied Math, Physics, Statistics)
- Experience with containerization (Docker, Kubernetes), CI/CD pipelines, and infrastructure-as-code frameworks
- Experience deploying and managing ML applications in cloud environments (AWS/GCP/Azure), including cloud-based storage, processing, and inference
- Experience shipping end-to-end ML applications from artifact to production, ideally in safety-critical or high-scale domains
- Expertise optimizing distributed model training with GPUs
Benefits
- Initial RSU grant with no vesting cliff
- Ongoing refresh opportunities tied to performance, subject to plan terms and conditions
- Performance-based bonus/variable pay
- Equity for eligible roles
- A flexible, employee-led remote model
- Professional development stipend
- Comprehensive health plans
- Parental leave plans
- Flexible working model supporting remote work
- Office access for those who prefer to work in-person
Company Overview