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As a Senior Machine Learning Engineer (Tech Lead), you'll lead the ML technical direction, design architectures for loco-manipulation, mentor team members, and manage cross-functional partnerships while writing production-quality code.

The Machine Learning Engineer will build a robot-learning stack, design training infrastructure, deploy ML policies, and collaborate with engineers in heavy manufacturing.

The Machine Learning Engineer will develop and deploy AI systems for robotics, focusing on advanced manipulation techniques and control algorithms, collaborating across teams.

The Technical Marketing Engineer will create technical content, collaborate with engineering teams, and ensure marketing material is credible for manufacturing audiences.

The Sales Enablement & Content Specialist will empower sales teams by creating content, training, and processes. They will enhance sales effectiveness through documented methodologies, program design, and ongoing analysis of enablement performance.

The Customer Success Manager will support defense industry customers, ensuring product implementation, cross-functional alignment, and long-term success of robotic systems.

As a Senior Machine Learning Engineer, you'll lead the development of a neural welding simulator, integrating research and production to enhance robotic systems. Responsibilities include building predictive models, collaborating with reinforcement learning engineers, and translating prototypes into maintainable production code.

The Senior Product Marketing Manager owns product positioning, drives go-to-market strategies, creates sales enablement materials, and collaborates cross-functionally to effectively launch and position products in the automation and manufacturing technology market.

The Robotic Operations Support Specialist will support customers by maintaining and troubleshooting autonomous welding cells, ensuring efficient operation and coordinating with engineering teams.

The Sr. Data Engineer will architect and build an end-to-end data platform, developing data pipelines and infrastructure for AI and robotics teams, ensuring data integrity and governance, and collaborating on ML model development.