As Senior Technical Manager on the Central Software ML Platform team, you'll oversee infrastructure used by machine learning (ML) engineers across Boston Dynamics. In this role, you'll spearhead design, implementation, and operations of infrastructure, unifying how ML/RL product and research teams get stuff done. If you are passionate about accelerating ML capabilities to create the world's most capable robots, we invite you to apply.
How you will make an impact: Build a robust ML platform supporting the end-to-end ML lifecycle, from early exploration through to fielded solutions. Own the overall design and long-term growth of an ML platform, including data management, compute capabilities, system deployment, and operationalization. Lead a team of ML engineers and platform specialists, fostering a collaborative, accountable work environment. Work closely with stakeholders across Boston Dynamics to identify critical directions, understand requirements, and prioritize needs. Propose and communicate roadmaps, schedules, and design concepts. Serve as a technical resource to your team and stakeholders across BD. Collaborate with security teams to ensure the platform meets industry standards and enforces security best practices. Develop comprehensive ML platform documentation, including guidelines, best practices, and training materials. Stay abreast of the latest advancements in ML technologies and choose appropriate tools and frameworks to enhance the platform's capabilities. You bring: 7+ years industry experience designing and implementing ML infrastructure. 5+ years leading, managing and mentoring teams in the ML space. Demonstrated experience gathering requirements, structuring deliverables, and managing agile projects. Ability to work collaboratively in cross-functional teams. Excellent communication and interpersonal skills. Proven track record developing, debugging, and deploying complex applications in Python, Julia, C++ or equivalent. Strong expertise in ML infrastructure technologies (e.g., k8s, Docker, PyTorch, Airflow, etc.). Experience using hybrid infrastructure, combining on-prem and cloud (GCP, AWS, Azure) resources, for ML applications. Familiarity with ML libraries/frameworks (PyTorch, Tensorflow, Keras, Pandas, Numpy) usage and deployment. Masters' Degree in Computer Science, Machine Learning, or a related field - or equivalent industry experience. This position does have the opportunity to be remote.
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