ML Ops Engineer

# Staff ML Ops Engineer Boston Dynamics Waltham Office (POST)
Full-time $150,000 – $180,000 / yearAI tools:

Py Torch Tensor Flow MLflow

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You’ll build and operate ML platform infrastructure and pipelines used by Boston Dynamics’ product and research teams. The work includes GPU cluster management, model deployment, monitoring, and improving data, training, and evaluation workflows.
* Permanent* On-site
* 5+ years
* Bachelor’s degree or equivalent practical experience### Skills and expertise

Python Py Torch Tensor Flow Docker Kubernetes GCPAWSSlurm### Key responsibilities
* Build and maintain ML infrastructure, deployment pipelines, and GPU cluster automation.
* Monitor platform health, troubleshoot issues, and improve cluster reliability.
* Profile and optimize data, training, and evaluation pipelines.## How this job compares

Compared with 96 open staff infrastructure jobs on October 10, 2026.Pay:
This job pays $150K to $180K a year. The 51 open staff infrastructure jobs that publish US pay start at $206K on average, so this job starts about 27% lower.

Similar open jobs:
We Love AI Jobs lists 96 open staff infrastructure jobs at 59 companies.

Remote work:
This job is on site. 17 of the 96 staff infrastructure jobs (18%) are remote.

AI in this role:
Medium. The role uses AI tools and works with AI systems as a regular part of the job. The role regularly supports ML and reinforcement-learning teams through infrastructure, deployment, and model pipelines. Its focus is platform engineering rather than building or training models directly.## Full description

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.

How you will make an impact
• 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

You bring
• 5+ years of experience as a Senior Software Engineer or ML Engineer
• Proficiency in Python and related ML frameworks (PyTorch, Tensor Flow, Pandas, Num Py)
• 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…