Strategic Overview
Staff ML Systems Engineer at Quilter is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Design, build, and maintain ML infrastructure across training, evaluation, serving, and monitoring Own data pipelines including generation, cleaning, validation, and versioning.
The role is listed for United States with remote working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Software Engineering, Senior.
Key information at a glance
About This Role
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.
Key Responsibilities & Objectives
- Design, build, and maintain ML infrastructure across training, evaluation, serving, and monitoring
- Own data pipelines including generation, cleaning, validation, and versioning
- Build and improve experiment tracking, orchestration, and reproducibility tooling
- Implement and maintain CI/CD pipelines and A/B testing infrastructure
Required Qualifications & Candidate Blueprint
- 7+ years of industry experience building and operating ML systems in production
- Proven track record as a key player in the success of a production-grade ML system end-to-end
- Deep familiarity with training pipelines, serving infrastructure, and experiment management
Preferred Qualifications
- 7+ years of industry experience
- Familiarity with ML workflows involving optimization, RL, or combinatorial problems
- Experience building infrastructure for small, research-heavy teams
Salary & Benefits
Published compensation: USD 180,000 – 200,000 / yearly
- 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
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Staff level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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 or Staff ML Systems Engineer to join Quilter's Placer Team and build the infrastructure that moves research from prototype to production reliably and efficiently.
The Role
The Placer is responsible for automated component placement on PCBs. This role focuses on the systems and infrastructure that support the full ML lifecycle: training pipelines, data generation and cleaning, experiment management, orchestration, serving, A/B testing, and CI/CD.
You'll be building the infrastructure that moves research from prototype to production reliably and efficiently. You'll also play a key role in systems design review and long-range architectural planning as the team scales.
This is a fully distributed team. We expect high autonomy and high ownership.
What Youʼll Do
Design, build, and maintain ML infrastructure across training, evaluation, serving, and monitoring
Own data pipelines including generation, cleaning, validation, and versioning
Build and improve experiment tracking, orchestration, and reproducibility tooling
Implement and maintain CI/CD pipelines and A/B testing infrastructure
Lead and formalize design review processes across the team
Identify architectural risks early and guide the team toward sustainable systems decisions
What Weʼre Looking For
7+ years of industry experience building and operating ML systems in production
Proven track record as a key player in the success of a production-grade ML system end-to-end
Deep familiarity with training pipelines, serving infrastructure, and experiment management
Strong software engineering fundamentals and systems design sensibility
Experience driving design reviews and improving engineering processes within a team
Comfort operating with high autonomy in ambiguous problem spaces
Experience with GPU-accelerated workloads and orchestration
Strong communication and collaboration skills
Preferred
7+ years of industry experience
Familiarity with ML workflows involving optimization, RL, or combinatorial problems
Experience building infrastructure for small, research-heavy teams
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches Software Engineering, Senior. Its strongest career signal is the scope of the work itself — particularly Design, build, and maintain ML infrastructure across training, evaluation, serving, and monitoring — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground Software Engineering, Senior, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.