Remote job
Senior ML Engineer
Job details
About this role
Role overview A senior-level machine learning engineer is needed to join a focused engineering team building AI that automates the placement of components on printed circuit boards. The work combines research and production engineering on a hard, real-world combinatorial problem spanning optimization, machine learning, and geometric deep learning. The position sits inside a fully distributed organization that expects high autonomy and strong end-to-end ownership.
Responsibilities - Drive problems end to end, from exploratory research and prototyping through productionized, maintainable systems - Develop and extend GPU-accelerated code in PyTorch and CUDA C++ - Explore a broad modeling landscape including reinforcement learning, graph neural networks, classical and black-box optimization, and generative modeling - Formulate objectives, encode constraints, and debug numerical behavior across the modeling and training stack - Partner with senior teammates to shape technical direction and research strategy
Requirements - Five or more years of industry experience in machine learning, optimization, or a closely related field - Strong fundamentals in machine learning and optimization theory - Hands-on, production-level experience with PyTorch - Demonstrated ability to operate across both research and production codebases - Comfort working with high autonomy in ambiguous problem spaces - Strong communication and collaboration skills
Nice to have - Five to seven years of relevant industry experience, with potential consideration at the staff level - CUDA C++ programming experience - Background in any combination of reinforcement learning, geometric deep learning, graph neural networks, multi-objective optimization, or combinatorial optimization
Benefits and work setup - Competitive compensation including salary and equity - Health, dental, and vision insurance - Regular team events and offsites, roughly four times per year - Unlimited paid time off - Paid parental leave - Fully distributed team structure