Staff ML Ops Engineer (opens in new tab)

Boston Dynamics; Waltham (MA); On-site; USD 150,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401(k)

Paid time off

Annual bonus

Job summary

Boston Dynamics in Waltham, MA, seeks a Staff ML Ops Engineer to join the Central Software ML Platform team. You will build tools, infrastructure, and pipelines that empower product and research teams to deploy models and scale AI capabilities for robotics.

You will own end-to-end delivery, maintain GPU clusters, implement observability, and collaborate with ML/RL engineers. A strong background in Python, ML frameworks, cloud deployment, and ML data workflows is required.

Qualifications

• 5+ years of experience as Software/ML Engineer
• Proficiency in Python and ML frameworks such as PyTorch/TensorFlow
• Experience with cloud platforms (GCP/AWS) and scalable ML deployment
• Experience with GPU clusters and scheduling systems
• Experience with CI/CD for ML pipelines
• Experience with experiment tracking and model/data versioning tools
• Experience building scalable data/ETL pipelines and data processing
• Experience with Agile, Scrum, or lean methodologies
• Bachelor's degree in Engineering, CS, or related field or equivalent
• Nice to have any of: networking basics, TS/Node, edge deployment

Responsibilities

• Transform proofs of concept into scalable solutions for product teams
• Scale fielded solutions and enable continuous model improvement
• Collaborate with BD stakeholders to meet end-user needs
• Own end-to-end delivery from implementation to deployment
• Maintain GPU clusters and automate health monitoring
• Use observability tools to diagnose system health and root causes
• Profile and optimize ML data, training, and evaluation pipelines
• Collaborate with ML Platform team to deploy ML infrastructure
• Participate actively in agile development and team planning
• Mentor and upskill peers across the organization

Skills

Python programming

ML framework experience

Cross-functional collaboration

Agile / Scrum

Experiment tracking

Data wrangling / ETL

Education

Bachelor's degree in Engineering or CS

Tools

Docker

Kubernetes

Ansible

Terraform

MLflow

Weights & Biases

DVC

Airflow

Spark

Job description

Staff ML Ops Engineer page is loaded## Staff ML Ops Engineerlocations: Waltham Office (POST)time type: Full timeposted on: Posted Yesterdayjob requisition id: R3202As 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, 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 have*** 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-TrackerWe are interested in all qualified candidates eligible to work in the United States. However, we are not able to sponsor visas for this position.The base pay range for this position is between $150,000 to $180,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.