ML/AI Engineer

Responsibilities

• Lead and contribute to cutting-edge research and engineering problems at the frontier of robotic AI, including approaches and systems that have not been built before.
• Explore and develop new learning methods, architectures, and training strategies for robots facing unseen scenarios.
• Turn research ideas into deployed robot behavior, bridging theory and real-world performance.
• Collaborate with cross-functional teams spanning robotics software, hardware, data, and infrastructure.
• Influence technical direction and system design in a fast-moving startup environment.
• Access large-scale data, compute, and modern ML infrastructure to train and evaluate advanced models.
• Grow through ownership of open-ended problems where solutions are not predefined.

Qualifications

• Degree in Computer Science, Electrical Engineering, or related field with focus on Deep Learning or Machine Learning.
• Solid understanding of machine learning fundamentals and modern deep learning techniques, with hands-on experience with ML frameworks such as PyTorch or TensorFlow.
• Strong programming skills, primarily in Python, with experience or willingness to work in C++-based robotics environments.
• Comfort working on open-ended, ambiguous problems where requirements and solutions evolve and curiosity and readiness to tackle new technical challenges that may not have established best practices.
• Experience working with real-world data, including noise, edge cases, and imperfect labels.
• Familiarity with robotics concepts such as perception, control, state estimation, or simulation a plus.
• Strong problem-solving skills and the ability to reason about complex systems.
• Able to collaborate effectively in fast-paced, research-driven environments.
• Clear communication skills and a strong sense of ownership over outcomes.