Hardware Machine Learning Engineer

Sourced from builtinchicago.org

Deploy machine learning directly onto custom hardware at IMC Trading. You will architect ML models with traders and engineers, shape the hardware roadmap, and implement inference solutions. Requires understanding of hardware constraints and ML fundamentals.

• Architect and co-design ML models with traders, quant researchers, and software engineers, treating hardware constraints as first-class design inputs
• Shape our custom hardware roadmap by translating ML model requirements into concrete architectural decisions
• Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production
• Track and evaluate emerging research in neural architecture search, machine learning systems and quantization methods

• Solid understanding of hardware constraints and design trade-offs (e.g., pipelining, resource utilization, fixed-point arithmetic)
• Experience with hardware fundamentals through VHDL/SystemVerilog development, HLS tools, or ML-to-hardware frameworks like hls4ml, FINN, or Vitis AI
• Understanding of machine learning fundamentals - neural network architectures, inference optimization, quantization techniques, ML frameworks such as PyTorch/TensorFlow