Hardware Machine Learning Engineer

Chicagofull timeOn Site

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$200k–$225k

H1B: no

Imc Hardware Machine Learning Engineer role at Imc involves architecting ML models with hardware constraints and collaborating with hardware engineers to deploy ML inference solutions. The role influences custom hardware roadmap and evaluates emerging ML research for system improvements.

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
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

Qualification

Proficiency in PythonAdvanced degree (MS or PhD) in EE$200

Required

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
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

Preferred

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 insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.
$200,000—$225,000 USD
IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

Company

Imc

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