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Remote position

Senior ML Engineer

at Quilter

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Fully remote ● Posted yesterday USA 180000-200000 USD Data

About this role

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:

  1. Focus on the mission

  2. Build great things that help humans

  3. Demonstrate grit

  4. Never stop learning

  5. 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

  • 5+ 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.

Real Remote Score 67/100 · see the full breakdown

Real Remote Score

67/100

Solid

Comp
25/25
Location
4/25
Source
10/15
Clarity
8/15
Freshness
20/20
Why this score? ▾
  • Compensation · Full salary range disclosed 25/25
  • Location · Specific city or narrow scope 4/25
  • Source · Remote-first job board 10/15
  • Role clarity · Seniority clear, stack not in title 8/15
  • Freshness · Posted yesterday 20/20

How the Real Remote Score is calculated → · Score appeals & corrections

Salary in context

About 16% below median for Data/ML

Listing floor: $180,000 · Role median across 127 peers: $215,000 · 25th–75th: $162,800–$250,000

Numbers refresh from the live corpus. Compare the full distribution at /tools/salary-index/ or run a city PPP adjustment at /tools/salary-calculator/.

Posted via Jobicy. Applications are handled by Quilter. RemNavi earns no commission.

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