ML Systems Engineer, Model Architectures

Skills

About the Role

You will get new model architectures running on the hardware first, in simulation. You will implement operators, numerics and memory layouts bit-exact against reference implementations, extend simulator coverage across the inference path, evaluate new architectures, bring up customer models and help automate that process.

Requirements

• 4+ years as an ML systems or inference engineer
• Strong understanding of transformer internals including attention variants, MoE, embeddings, KV cache and quantization (INT8, FP8)
• Experience implementing or porting model inference in PyTorch, llama.cpp, vLLM, TensorRT-LLM or a custom runtime
• Experience debugging numerical mismatches down to the bit
• Ability to turn architecture papers into verified implementations
• Strong Rust skills or expert C/C++ with willingness to use Rust, and strong Python skills
• Excellent communication skills

Responsibilities

• Implement operators, numerics and memory layouts for new model architectures bit-exact against a reference
• Extend simulator coverage across prefill, decode, embeddings, attention variants, mixture-of-experts routing and quantized formats
• Maintain reference comparisons and regression coverage
• Evaluate new architectures for compute, memory and data movement needs
• Bring customer models up in simulation and own turnaround time
• Partner on automating new-model bring-up end to end

Benefits

• Fully company-paid medical, dental and vision insurance for you and dependents
• Company-paid life and disability coverage
• Supplemental hospital, critical illness and accident coverage available
• Unlimited paid time off
• 13 paid company holidays
• Remote-first culture with company-provided computer and home office setup
• Equity
• 401(k) with company matching from day one