Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Senior ML Engineer
Remote - US · Los Angeles, California, USA
Open 5 months, first seen by us 164 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
Remote — work setting source
Location type: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require employment visa sponsorship to work in the United States or Canada?
From the employer’s application form
What you’ll work on
Full postingOwn problems end-to-end from exploratory R&D to production systems
Develop and extend GPU-accelerated code in PyTorch and CUDA C++
Model problems with RL, graph neural networks, and optimization methods
Formulate objectives, model constraints, and debug numerical behavior
Shape technical direction and research strategy with senior teammates
From the employer’s posting
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 you’ll bring
All qualificationsCore experience
- 5+ years of industry experience in ML, optimization, or related field
- Strong fundamentals in machine learning and optimization
- Production PyTorch experience
- Ability to work across research and production codebases
- Comfort working with high autonomy in ambiguous problem spaces
Qualification wording
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
Benefits in the posting
Full benefits wording- Interesting and challenging work
- Competitive salary and equity benefits
- Health, dental, and vision insurance
- 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.
From the employer’s posting.
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).
In the employer’s words · Read in context · Company website ↗
Posting record
Report an errorOpen 5 monthsWe first saw this posting 164 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026164 days ago
- Recorded sightings
- 81
- Last seen by us
- Nov 13, 2026
- Employer says posted
- Apr 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 164
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past Quilter’s usual: its jobs come down by about day 27.
From 5,461 similar postings that came down, and 13 of Quilter’s. Coming down is not always a hire.
Quilter is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
- 25% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- C++
- PyTorch
Where the posting names them
- 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
- 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
- Strong fundamentals in machine learning and optimization - Production PyTorch experience - Demonstrated ability to work across research and production codebases
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Applying through Ashby
- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
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:
Curiosity
Conviction
Rigor
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.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Los Angeles, California, USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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