Senior/Staff ML Systems Engineer

🕒 April 3

🇺🇸 United States – Remote

💵 $180k - $200k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 52%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Quilter

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

🏭 Manufacturing

🔧 Hardware

Consulting • Manufacturing • Hardware

Quilter is an innovative technology company offering an all-in-one PCB design tool tailored for hardware teams. This platform enables engineers to automate and optimize circuit board layouts, reducing design time from weeks to mere hours. Quilter's software is compatible with existing design tools like Altium and KiCAD, and it imports design constraints to optimize for EMI performance and manufacturing. Offering generative AI-driven design processes, Quilter provides numerous quality design candidates that are production-ready. The company's "Fab for Free" program and open beta version make it a cost-effective choice for electronics companies worldwide.

📋 Description

• 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

🎯 Requirements

• 5+ 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

🏖️ Benefits

• Health, dental, and vision insurance • Unlimited paid time off • Paid parental leave • Regular team events and offsites (~4x / year)