Senior Scaled ML Engineer (Los Angeles)

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 $10 million in series-A 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

Were looking for a Senior Scaled ML Engineer to join Quilters ML Team and help us build the software platform behind the future of circuit board design. We are a team of generalists who pride ourselves on solving new challenges and always learning. As one of our early engineers, youll have massive ownership and influence over the direction of our product, architecture, and team culture.

This role is ideal for someone who thrives in high-ownership environments, loves solving complex technical problems, and is excited by the idea of bridging the worlds of software and hardware development.

What You?ll Do

Develop and train large-scale ML models for PCB layout automation

Implement efficient and reliable training pipelines for geometric and spatial datasets

Research and develop novel architectures for circuit board optimization

Optimize models for both accuracy and low-latency inference

Collaborate on data pipeline design for PCB and schematic datasets

What We?re Looking For

Experience with large-scale training of models with 100M+ parameters

Expertise in distributed training using PyTorch across multi-GPU and multi-node environments

Knowledge of memory optimization techniques such as gradient checkpointing, mixed precision, and parameter sharding

Familiarity of training infrastructure including cluster management and job scheduling systems

Background in model architecture design across transformers, CNNs, and graph networks for geometric data

Experience with performance optimization focused on training speed, convergence, and scaling laws

Nice to Have

Experience with Reinforcement Learning - combinatorial / constrained optimization problems, sequential decision-making.

Knowledge of Model Compression Techniques - knowledge distillation, pruning strategies, etc.

Expertise with Attention Mechanisms - specifically spatial / geometric attention

ML Tooling Experience - NVIDIA Nsight, PyTorch profiler, Weights & Biases

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 (~2x / 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.