Senior ML Engineer - Remote Eligible

Senior ML Engineer

We're looking for a Senior ML Engineer to join Quilter's Placer Team and help us build the AI that automates component placement on PCBs.

The Placer is responsible for automated component placement on PCBs. This role spans the full lifecycle: research, prototyping, productionization, and maintenance. You'll work across optimization, machine learning, and geometric deep learning on a hard, real-world combinatorial problem.

This is a fully distributed team. We expect high autonomy and high ownership.

What You'll Do:

• Own problems end-to-end from exploratory R&D through production-hardened, maintainable systems
• Develop and extend GPU-accelerated code in PyTorch and CUDA C++
• Work across a broad modeling landscape including RL, graph neural networks, black-box/classical optimization, and generative modeling
• Formulate objectives, model constraints, and debug numerical behavior in the stack
• Contribute to technical direction and research strategy alongside senior teammates

What We're Looking For:

• 4+ years of industry experience in ML, optimization, or a related field
• Strong fundamentals in machine learning and optimization
• Production PyTorch experience
• Demonstrated ability to work across research and production codebases
• Comfort operating with high autonomy in ambiguous problem spaces
• Strong communication and collaboration skills

Preferred:

• 5–7 years of industry experience (Staff-level appointment may be considered)
• CUDA C++ experience
• Background in any combination of: reinforcement learning, geometric deep learning, graph neural networks, multi-objective optimization, combinatorial optimization

Please note: We are an equal opportunity employer. At this time, we are focused on hiring primarily within the US, with occasional exception to accommodate exceptional talent.

What We Offer:

• Interesting and challenging work
• Competitive salary and equity benefits
• Health, dental, and vision insurance
• Regular team events and offsites (~4x / year)
• Unlimited paid time off
• Paid parental leave