Job description
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
We’re looking for a Senior Scaled ML Engineer to join Quilter’s 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, you’ll 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 Youʼll 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 Weʼre 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.
