Hardware Machine Learning Engineer
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Job Location:
Chicago, IL - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
We are deploying machine learning directly onto custom hardware and we want you to help drive it from the ground up. This is an initiative where youll have the rare opportunity to architect solutions from scratch influence technical research direction and see your work drive real impact in one of the most demanding computing environments in the world.
We build the hardware the software and the infrastructure so when you hit a bottleneck you can fix it - theres no vendor to wait on and no abstraction layer youre not allowed to touch. If youve ever wanted to push the boundaries of whats computationally possible this role is for you. Were looking for researchers and experienced engineers from any background. Trading experience is a bonus not a prerequisite.
Your Core Responsibilities
- Architect and co-design ML models with traders quant researchers and software engineers treating hardware constraints (latency budgets resource limits numerical precision) 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 and determine what translates to measurable improvements in our systems
Your Skills and Experience
- Solid understanding of hardware constraints and design trade-offs (e.g. pipelining resource utilization fixed-point arithmetic) that shape how ML models can be efficiently mapped onto FPGAs or custom ASICs
- Experience with hardware fundamentals whether 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
- Proficiency in Python C or similar languages for tooling testing and simulation
- Strong communication skills and ability to work collaboratively across disciplines with both technical and non-technical teams
Nice to Have
- Exposure to ML compiler infrastructure such as MLIR TVM XLA or similar tools for lowering and optimizing models for hardware targets
- Background in latency-sensitive or resource-constrained systems including high-frequency trading particle physics data acquisition real-time signal processing or similar domains
- Familiarity with functional verification methodologies (for example SystemVerilog UVM Cocotb)
- Advanced degree (MS or PhD) in EE CS Physics or related field or equivalent depth through industry or research experience
The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time permanent positions are eligible for a discretionary bonus and benefits including paid leave and visit Benefits - US IMC Trading for more comprehensive information.
About Us
IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989 weve been a stabilizing force in financial markets providing essential liquidity upon which market participants depend. Across our offices in the US Europe Asia Pacific and India our talented quant researchers engineers traders and business operations professionals are united by our uniquely collaborative high-performance culture and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies and from developing an innovative research environment to diversifying our trading strategies we dare to continuously innovate and collaborate to succeed.
Required Experience:
IC
Key Skills
About Company
0-50 employees
IMC is where the brightest minds in trading, technology, and quant research come together to solve the industry’s greatest challenges. Explore careers with us.
