Senior Machine Learning Engineer – ML at Scale

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September 20

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Quilter

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Hardware • SaaS • Artificial Intelligence

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.

2 - 10 employees

🔧 Hardware

☁️ SaaS

🤖 Artificial Intelligence

📋 Description

• 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 • Take significant ownership over product, architecture, and team culture as an early engineer

🎯 Requirements

• 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 for combinatorial/constrained optimization and sequential decision-making • (Nice to have) Knowledge of Model Compression Techniques such as knowledge distillation and pruning strategies • (Nice to have) Expertise with Attention Mechanisms, specifically spatial/geometric attention • (Nice to have) ML Tooling Experience: NVIDIA Nsight, PyTorch profiler, Weights & Biases

🏖️ Benefits

• 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