Staff MLOps Engineer — On‑Site GPU Platform Lead

We Love AI Jobs; Waltham (MA); Hybrid; USD 150,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k)

Paid time off

Annual bonus

Job summary

Boston Dynamics is seeking a Staff MLOps Engineer to design and operate ML platform infrastructure and pipelines for product and research teams in Waltham. You will manage GPU clusters, deployment pipelines, and model workflows, ensuring scalable, reliable systems.

The role emphasizes end-to-end delivery, observability, and collaboration with BD engineers and researchers to push robotics AI capabilities forward.

Qualifications

• 5+ years of experience as a Senior Software Engineer or ML Engineer.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Experience with cloud platforms (GCP, AWS) and container orchestration (Docker, Kubernetes).

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.
• Own end-to-end delivery of new capabilities, spanning implementation, testing, deployment, and operations.
• Maintain 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.
• Collaborate with ML Platform team to deploy and maintain ML infrastructure.
• Participate in agile development, coordinate with teams, and mentor peers.

Skills

Python

PyTorch

TensorFlow

Docker

Kubernetes

GCP

AWS

Slurm

Education

Bachelor's degree

Tools

MLflow

Weights & Biases

DVC

Spark

Airflow

Terraform

Job description

Boston Dynamics is seeking a Staff MLOps Engineer to design and operate ML platform infrastructure and pipelines for product and research teams in Waltham. You will manage GPU clusters, deployment pipelines, and model workflows, ensuring scalable, reliable systems.

The role emphasizes end-to-end delivery, observability, and collaboration with BD engineers and researchers to push robotics AI capabilities forward.