Staff ML Ops Engineer

Boston Dynamics•Waltham, MA

6d•$150,000 - $180,000

About The Position

As an MLOps Engineer on the Central Software (CSW) ML Platform team, you will play an active role in implementing the tools, infrastructure, and pipelines that unify how our product and research teams get stuff done. This is your chance to work closely with ML/RL engineers and researchers from across Boston Dynamics (BD), supporting advanced AI product and research activities at the forefront of robotics innovation.

Requirements

5+ years of experience as a Senior Software Engineer or ML Engineer
Proficiency in Python and related ML frameworks (PyTorch, TensorFlow, Pandas, NumPy)
Experience with cloud platforms (e.g., GCP, AWS) and scalable ML deployment methods (Docker, Kubernetes, Ansible, Terraform)
Experience with GPU cluster management and scheduling (e.g., Slurm, Kueue, or similar)
Experience with CI/CD practices applied to ML pipelines
Experience with experiment tracking and model/data versioning tools (e.g., MLflow, Weights & Biases, DVC)
Experience building scalable data and ETL pipelines (e.g., Spark, Airflow) alongside data processing, augmentation, and cleaning techniques.
Experience with Agile, Scrum, or other lean methodologies; ability to work collaboratively in cross-functional teams
Bachelor's degree in Engineering, Computer Science, or a related technical field, or equivalent practical experience

Nice To Haves

Experience with networking fundamentals such as IAP, Tailscale, Shared VPC, NAT
Familiarity with database optimization concepts such as indexing and connection pooling.
Experience with TypeScript, Node, and related full-stack web technologies to build internal tooling, visualization dashboards, and web-based interfaces for MLOps platforms
Experience with on-robot/edge deployment constraints (latency, compute limits, OTA model updates)
Experience with annotation tools such as SAM or Co-Tracker

Responsibilities

Transform proofs of concept into scalable solutions, helping product teams deliver new robot capabilities to customers
Evolve and scale fielded solutions, enabling continuous model improvement and redeployment
Work with stakeholders across BD to understand requirements, ensuring deployed solutions meet end-user needs
Own end-to-end delivery of new capabilities, spanning implementation, testing, deployment, and operations
Maintain our GPU clusters and develop automation to monitor and improve cluster health
Use observability tools to monitor system health and root-cause problems across the platform
Drive accuracy and efficiency by profiling and optimizing ML data, training, and evaluation pipelines.
Work closely with other members of the ML Platform team to implement, deploy, and maintain ML infrastructure
Be an active participant in our agile development process, coordinating work with others, calling out challenges, and regularly communicating progress
Use your experience to mentor and upskill peers and other contributors across the organization