About Quilter

At Quilter, we are helping electrical engineers save time and accomplish more by automating the tedious and time-consuming task of designing printed circuit boards (PCBs). Our small team is composed of experts in electrical engineering, electromagnetic simulation, ML/AI, and high-performance computing (HPC). We are inventing and leveraging novel techniques to solve the decades-old problem of automating circuit board design where today hundreds of billions of dollars are spent. We have raised $25 million in Series B funding from some of the very best and are charging full-speed toward our goal.

No matter where we come from, we're united by a common vision for the future and a core set of values we think will get us there:

Focus on the mission

Build great things that help humans

Demonstrate grit

Never stop learning

Pursue excellence

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 Role

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 Youʼll 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 Weʼre 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

      Want to learn more about Quilter, our vision, and our investors? Visit our About page and visit our Blog.