Senior MLOps Engineer

Teleo • Palo Alto, CA

5d • $200,000 - $250,000

About The Position

Own the reliability, scalability, and velocity of model training and deployment for autonomy systems. Turn experimental models into dependable production services.

Requirements

• 2+ years in MLOps / Infra / ML Platform
• Deep experience with PyTorch, CUDA-aware workflows
• Strong Linux + systems fundamentals
• Proven experience deploying models at scale (not just notebooks)

Nice To Haves

• Training orchestration: Ray, Slurm, Kubernetes, Airflow
• Model lifecycle: Weights & Biases, MLflow, custom registries
• Containers: Docker, multi-arch builds
• Inference optimization: TensorRT, ONNX, Triton
• Monitoring: metrics, logs, alerts for ML systems
• Experience with autonomy or robotics
• Edge deployment constraints (latency, power, thermal)
• Data versioning tools (DVC, LakeFS)

Responsibilities

• Design and operate end-to-end ML infrastructure: training, evaluation, deployment, monitoring
• Build CI/CD for ML (model versioning, promotion, rollback, canarying)
• Own model observability: drift detection, performance regression, data health
• Optimize GPU utilization across training and inference (on-prem + cloud)
• Support edge deployment (Jetson / Orin / x86 + GPU)
• Work closely with perception and autonomy teams to reduce friction from research to production

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed