jobctl

Senior ML Engineer

Quilter - USA - original posting ->
Status
Open
Remote policy
Not stated
Employment type
Full-time
Salary
Not stated
Categories
Software Engineering
Tech
cppmlsenior
Source
jobicy
First observed
2026-08-25 19:15 UTC
Last seen
2026-10-26 08:24 UTC
Source claims posted
2026-10-26 04:07 UTC
Consecutive misses
0 of 10

What the posting says

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

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.

Quality

Completeness: 45%
Honesty: 70%

Based on 27 observation(s).

Timeline

  1. *
    #366271 2026-08-25 19:15 UTC
    Published
  2. o
    #385667 2026-08-26 18:30 UTC
    Not seen
    Miss 1 in a row
  3. o
    #386707 2026-08-26 19:30 UTC
    Not seen
    Miss 2 in a row
  4. o
    #386806 2026-08-26 20:32 UTC
    Not seen
    Miss 3 in a row
  5. o
    #386930 2026-08-26 21:32 UTC
    Not seen
    Miss 4 in a row
  6. o
    #387518 2026-08-26 22:34 UTC
    Not seen
    Miss 5 in a row
  7. o
    #389819 2026-08-26 23:34 UTC
    Not seen
    Miss 6 in a row
  8. o
    #390307 2026-08-27 00:36 UTC
    Not seen
    Miss 7 in a row
  9. o
    #390878 2026-08-27 01:36 UTC
    Not seen
    Miss 8 in a row
  10. o
    #391623 2026-08-27 02:38 UTC
    Not seen
    Miss 9 in a row
  11. o
    #392671 2026-08-27 03:38 UTC
    Not seen
    Miss 10 in a row
  12. x
    #392672 2026-08-27 03:38 UTC
    Closed
  13. ^
    #1005257 2026-09-25 20:06 UTC
    Reopened
  14. ~
    #1005258 2026-09-25 20:06 UTC
    Modified
    • Posted at
      2026-08-25 14:25 UTC->2026-09-25 04:20 UTC
  15. o
    #1031436 2026-09-27 13:21 UTC
    Not seen
    Miss 1 in a row
  16. o
    #1032438 2026-09-27 14:25 UTC
    Not seen
    Miss 2 in a row
  17. o
    #1032973 2026-09-27 15:25 UTC
    Not seen
    Miss 3 in a row
  18. o
    #1033682 2026-09-27 16:28 UTC
    Not seen
    Miss 4 in a row
  19. o
    #1034071 2026-09-27 17:29 UTC
    Not seen
    Miss 5 in a row
  20. o
    #1034807 2026-09-27 18:37 UTC
    Not seen
    Miss 6 in a row
  21. o
    #1035431 2026-09-27 19:39 UTC
    Not seen
    Miss 7 in a row
  22. o
    #1035768 2026-09-27 20:41 UTC
    Not seen
    Miss 8 in a row
  23. o
    #1036202 2026-09-27 21:42 UTC
    Not seen
    Miss 9 in a row
  24. o
    #1037101 2026-09-27 22:44 UTC
    Not seen
    Miss 10 in a row
  25. x
    #1037102 2026-09-27 22:44 UTC
    Closed
  26. ^
    #1544549 2026-10-26 08:24 UTC
    Reopened
  27. ~
    #1544550 2026-10-26 08:24 UTC
    Modified
    • Posted at
      2026-09-25 04:20 UTC->2026-10-26 04:07 UTC