Hardware Machine Learning PhD Research Internship

About this role

Join IMC's hardware ML team as a PhD intern to research and develop machine learning inference solutions on custom hardware, working alongside engineers in a low-latency computing environment. You'll own a focused research project from conception to prototype, exploring neural architecture search, quantization, and hardware acceleration techniques with real-world impact.

What you'll do

• Design and execute an ML-focused research project grounded in real-world use cases and business constraints
• Collaborate with hardware engineers to implement, validate, and deploy ML inference on FPGAs or custom ASICs
• Evaluate emerging research in neural architecture search, ML systems, and quantization to identify practical improvements
• Develop and benchmark prototypes that demonstrate measurable performance gains
• Present research findings and insights to the team to advance collective knowledge
• Learn hardware design fundamentals from RTL developers and apply them to ML acceleration problems

What they're looking for

• Neural network architectures and inference optimization
• Quantization techniques and model compression
• VHDL/SystemVerilog or HLS tool experience
• ML-to-hardware frameworks (hls4ml, FINN, Vitis AI)
• PyTorch or TensorFlow
• Python for tooling, testing, and simulation
• Understanding of hardware constraints (pipelining, resource utilization, fixed-point arithmetic)
• Cross-disciplinary communication and collaboration

Benefits

• Discretionary bonus
• Paid leave
• Insurance coverage
• Mentorship from skilled hardware and ML engineers
• Exposure to real-world low-latency trading infrastructure
• Opportunity to publish research with industry relevance