Senior ML Engineer

📋 Job Overview

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.

🏢 About Quilter

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.

✅ Key Responsibilities

• 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

📌 Required Qualifications

• 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

⭐ Desirable Experience

• 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

🎁 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

🛂 Visa & Eligibility

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.