IMC Trading
Hardware Machine Learning PhD Research Internship
Eligibility
- Currently enrolled PhD student in relevant fields
PhD internship at IMC to conduct hardware and machine learning research for low-latency ML inference and hardware acceleration in trading technology.
Responsibilities
- Architect and develop an ML focused research project based on real-world use cases
- Work hands-on with hardware engineers to implement, verify, and deploy ML inference solutions
- Track and evaluate emerging research in neural architecture search, machine learning systems and quantization methods
- Present your project to the team, enhancing collective understanding of ML acceleration
- Gain hardware design fundamentals from RTL developers
- Build skills to evaluate research considering performance constraints, engineering costs, and industry impact
Requirements
- Currently enrolled in a PhD program in Electrical Engineering, Computer Science, Physics, or related field
- Solid understanding of hardware constraints and design trade-offs for ML models on FPGAs or ASICs
- Experience with VHDL/SystemVerilog, HLS tools, or ML-to-hardware frameworks like hls4ml, FINN, or Vitis AI
- Understanding of machine learning fundamentals including neural networks and quantization
- Proficiency in Python or similar languages for tooling and testing
- Strong communication and collaboration skills
Skills
- VHDL
- SystemVerilog
- HLS tools
- Python
- Machine learning (PyTorch, TensorFlow)
- Hardware design fundamentals
- Last checked