Staff ML Systems Engineer

The role

This person will build infrastructure that moves research from prototype to production. They will focus on the systems and infrastructure supporting the full ML lifecycle for automated component placement on PCBs.

What you will 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

Required qualifications

• 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

Nice to have

• 7+ years of industry experience
• Familiarity with ML workflows involving optimization, RL, or combinatorial problems
• Experience building infrastructure for small, research-heavy teams

Benefits

• 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

Before you apply

• focused on hiring primarily within the US, with occasional exception to accommodate exceptional talent

About the company

Quilter helps electrical engineers save time by automating the task of designing printed circuit boards (PCBs). The team is composed of experts in electrical engineering, electromagnetic simulation, ML/AI, and high-performance computing (HPC).