As Associate Director ML Platform on the Central Software team, you’ll spearhead development and expansion of machine learning (ML) capabilities at Boston Dynamics. You’ll oversee the design, implementation, and operations of infrastructure, and pipelines that unify how our many product ML/RL engineers and researchers get stuff done. If you are passionate about working with multidisciplinary teams to create the world’s most capable robots, we invite you to apply.

How you will make an impact:

• Build a robust ML platform that facilitates the end-to-end machine learning lifecycle, from data ingestion and model training to deployment and monitoring.

• Lead a team of ML engineers and platform specialists, providing mentorship, guidance, and fostering a collaborative, accountable, and innovative work environment.

• Stay abreast of the latest advancements in ML technologies and choose appropriate tools and frameworks to enhance the platform’s capabilities.

• Work closely with cross-functional teams, including ML research scientists, engineers, and business stakeholders to understand requirements and ensure the platform meets the diverse needs of the organization.

• Propose and communicate roadmaps, schedules.  Align stakeholders’ direction and priorities.

• Implement and enforce best practices for security, data privacy, and compliance within the machine learning platform. Collaborate with security teams to ensure the platform meets industry standards.

• Develop comprehensive ML platform documentation, including guidelines, best practices, and training materials. 

You bring:

• 10+ 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 projects in an agile environment.

• Strong expertise in ML infrastructure technologies (e.g., k8s, Docker, PyTorch, Airflow, etc.)

• Strong programming skills in Python or other commonly used ML languages

• Experience using hybrid infrastructure, combining on-prem and cloud (GCP, AWS, Azure) resources, for ML applications

• Excellent communication and interpersonal skills.

• Masters’ Degree in Computer Science, Machine Learning, or a related field - or equivalent industry experience

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