ML Ops Engineer, Central Software

Boston Dynamics’ mission is to image and create robots that enrich people’s lives. Our mobile robots operate in the most challenging and remote environments imaginable, from industrial sites to disaster zones. We are a passionate team of innovators, thinkers, and builders dedicated to creating products that our users love. 

To bolster our mission, we're looking for a talented ML Ops Engineer to join the Central Software (CSW) Machine Learning Platform team. In this role, you will play an active role in implementing, scaling, and extending the tools, infrastructure, and pipelines helping unify how our product and research teams leverage ML at Boston Dynamics. This is your chance to work closely with ML/RL engineers and researchers from across the company, supporting advanced product / research activities at the forefront of robotics innovation.

How you will make an impact:

• ML Operations: Evolve/scale/optimize fielded solutions and enable orchestration of ML training workloads on GPU clusters

• ML Infrastructure Support: Work closely with others to implement, deploy, and maintain ML infrastructure

• New Capabilities: Transform proofs of concepts into scalable solutions, helping deliver new robot capabilities to customers.

• Engagement: Work with stakeholders across BD to understand requirements, ensuring deployed solutions meet end-user needs

• Ownership: Own the end-to-end spanning implementation, testing, deploying, and monitoring.

• Coordination: Participate in agile development process, work with others, identify challenges, and regularly communicate progress

• Mentorship: Use your experience to mentor/upskill peers and other contributors across the organization

We're Looking For Someone With:

• 7+ years experience as an ML Platform engineer

• Demonstrated expert-level proficiency in Python (mandatory) and system programming (e.g., Go, C++, Rust)

• Demonstrated proficiency managing and configuring cloud resources Infrastructure as Code (e.g., Terraform, Ansible) 

• Expert in scalable ML deployments via kubernetes

• Hands-on knowledge of designing pipelines to automate code deployment, model training, and validation using Argo CD, CI, etc.

• Configuring and using observability metrics to drive improvements in system metrics (e.g., CPU/GPU/Latency/Performance)

• Experience managing/operating in hybrid hosted/on-prem compute environments 

• Experience working collaboratively in cross-functional team using Agile, Scrum, or other lean approach

• Bachelors in Engineering, Computer Science, or other technical area

Bonus Points If You Have:

• Experience with data processing, data augmentation, and data cleaning techniques 

• Knowledge of distributed computing & big data technologies for large datasets (e.g., Spark, Scala, etc.) and building data pipelines 

• Knowledge of ML-related frameworks (PyTorch, Tensorflow, Pandas, Numpy)

• Knowledge of Deep Learning methodologies specific to Computer Vision like YOLO Experience with Annotation tools using SAM, Co-Tracker, etc. 

If this appeals to you and you’re looking for a role that helps you make an impact, come join the team!