Hardware Machine Learning Engineer

IMC B.V.; Chicago (IL); On-site; USD 200,000 - 225,000; Full time

Benefits offered by this job

Discretionary bonus

Paid leave

Insurance benefits

Job summary

A global trading firm is seeking an experienced engineer to architect machine learning solutions directly on custom hardware. The role involves designing and deploying ML engines and collaborating with various teams. Ideal candidates will have solid experience with FPGA or ASIC technologies, proficiency in languages like Python or C++, and an advanced degree in a relevant field. This position offers a competitive salary ranging from $200,000 to $225,000, along with benefits and bonuses.

Qualifications

• Extensive FPGA or ASIC experience with VHDL, Verilog, or SystemVerilog.
• Solid digital design understanding including pipelining and clock domain crossing.
• Experience with FPGA tools like Vivado or Quartus.

Responsibilities

• Design and deploy machine learning engines on custom hardware.
• Collaborate with traders and researchers for ML model implementation.
• Shape a greenfield initiative with the freedom to explore novel approaches.

Skills

Extensive experience with FPGA or ASIC technologies

Solid understanding of digital design principles

Experience with FPGA development tools

Understanding of machine learning fundamentals

Experience optimizing inference for ML models

Proficiency in Python, C++, or similar languages

Strong communication skills

Education

Advanced degree (MS or PhD) in Electrical Engineering, Computer Science, Physics, or related field

Tools

Vivado

Quartus

Synplify

Job description

Overview

We are deploying machine learning directly onto custom hardware – and we want you to help shape it from the ground up. This is an initiative where you'll have the rare opportunity to architect solutions from scratch, influence technical direction, and see your work drive real impact in one of the most demanding computing environments in the world.

We already have one of the most competitive low latency setups in trading. Now, we're expanding our use cases to bring the power of neural networks and ML algorithms onto our custom hardware infrastructure. If you've ever wanted to push the boundaries of what's computationally possible, this role is for you.

Your Core Responsibilities

• Design, implement, and deploy machine learning engines on custom hardware, achieving latency that software alone cannot match
• Through HW/SW co-design, you’ll collaborate closely with traders, quantitative researchers, and software engineers to translate ML models into efficient implementations – combining the strengths of software with the strengths of hardware
• Shape a greenfield initiative from the ground up, with the freedom to explore novel approaches and set technical direction
• Research and build cutting-edge techniques for neural network quantization, compression, and tools that bridge high-level ML frameworks to RTL
• See the results of your work deployed in production within days, not months – our collaborative culture and unified global codebase enable rapid iteration

Your Skills and Experience

• Extensive experience with FPGA or ASIC technologies, including proficiency in either VHDL, Verilog, or SystemVerilog
• Solid understanding of digital design principles, including pipelining, flow control, and clock domain crossing
• Experience with FPGA development tools and toolchains (Vivado, Quartus, Synplify, etc.)
• Understanding of machine learning fundamentals – neural network architectures, inference optimization, quantization techniques
• Experience optimizing inference for temporal or sequential ML models (RNNs, Transformers, state-space models) on resource-constrained or latency-sensitive platforms
• 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

• Experience with High-Level Synthesis (HLS) or other hardware description languages beyond traditional RTL
• Familiarity with ML-to-hardware frameworks such as hls4ml, FINN, or Vitis AI
• Experience with ML-relevant compiler intermediate representations and optimization passes such as MLIR, LLVM, polyhedral analysis, or production ML compilers (TVM, XLA, IREE)
• Background in ultra-low-latency systems – whether in high-frequency trading, particle accelerator data acquisition, real-time signal processing, or similar applications
• Experience with functional verification methodologies (SystemVerilog, UVM, Cocotb)
• Advanced degree (MS or PhD) in Electrical Engineering, Computer Science, Physics, or related field

Compensation

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 information.

Salary Range

$200,000 — $225,000 USD

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve 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.