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Neural Engineer Jobs in Chicago, IL (NOW HIRING)

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

We're looking for researchers and experienced engineers from any background. Trading experience is ... Track and evaluate emerging research in neural architecture search, machine learning systems and ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

Track and evaluate emerging research in neural architecture search, machine learning systems and ... engineers, traders, and business operations professionals are united by our uniquely collaborative ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

Track and evaluate emerging research in neural architecture search, machine learning systems and ... engineers, traders, and business operations professionals are united by our uniquely collaborative ...

Contruent

AI Engineer

Naperville, IL · On-site

About the Role We are seeking a hands-on AI Engineer to help design, build, and deploy intelligent ... Experience mapping domain business problems into building deep neural networks for predictive ...

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Neural Engineer information

See Chicago, IL salary details

$61.3K

$115K

$209.1K

How much do neural engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for neural engineer in Chicago, IL is $114,997.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,900.00 and $136,500.00 per year, depending on experience, location, and employer.

What jobs can you do with neural engineering?

Neural engineers can work in research and development roles focused on brain-computer interfaces, neural prosthetics, and neurotechnology devices. They often work in healthcare, biotech, or academic settings, applying skills in signal processing, neuroscience, and biomedical engineering to develop innovative solutions for neurological disorders and neural interface systems.

What does a neural engineer do?

A neural engineer designs and develops technologies to interface with the nervous system, such as brain-computer interfaces and neural prosthetics. They often work with biomedical signals, use tools like MATLAB or Python, and require knowledge of neuroscience, engineering, and programming. Their work supports medical treatments, research, and the development of neural devices.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and aerospace engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often involves working in high-demand industries, holding managerial or executive positions, or possessing rare expertise and certifications.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and aerospace engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often involves bonuses, stock options, or profit sharing, particularly in technology and energy sectors.

What types of projects and collaborations can a Neural Engineer expect to be involved in?

As a Neural Engineer, you may work on projects ranging from designing brain-computer interfaces and neural prosthetics to analyzing complex neural signals for clinical or research applications. Collaboration with neuroscientists, clinicians, software developers, and hardware engineers is common, ensuring a multidisciplinary approach to solving neurological challenges. Your daily responsibilities might include data analysis, prototyping, testing devices, and presenting findings to your team. This role offers opportunities to influence cutting-edge research and directly contribute to advancements in healthcare and neurotechnology.

What does a Neural Engineer do?

A Neural Engineer applies principles from neuroscience, engineering, and computer science to develop technologies that interface with the nervous system. This includes designing brain-computer interfaces, neuroprosthetics, and medical devices for treating neurological disorders. They work with signal processing, machine learning, and biomedical hardware to understand and manipulate neural activity. Their work has applications in healthcare, rehabilitation, and human augmentation.

What are the key skills and qualifications needed to thrive in the Neural Engineer position, and why are they important?

To thrive as a Neural Engineer, you need a strong background in biomedical engineering, neuroscience, and signal processing, often supported by an advanced degree in a related field. Proficiency with tools like MATLAB, Python, neural data acquisition systems, and familiarity with medical device regulations or certifications are commonly required. Problem-solving abilities, interdisciplinary teamwork, and effective communication set standout candidates apart. These skills and qualities are crucial for innovating and safely developing neural devices and technologies that bridge engineering and neuroscience.

What are the most commonly searched types of Neural Engineer jobs in Chicago, IL? The most popular types of Neural Engineer jobs in Chicago, IL are:
What are popular job titles related to Neural Engineer jobs in Chicago, IL? For Neural Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Neural Engineer jobs in Chicago, IL look for? The top searched job categories for Neural Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Neural Engineer jobs? Cities near Chicago, IL with the most Neural Engineer job openings:
Neural Engineer jobs near you
Infographic showing various Neural Engineer job openings in Chicago, IL as of July 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% In-person job distribution, with an average salary of $114,997 per year, or $55.3 per hour.
Hardware Machine Learning Engineer

Hardware Machine Learning Engineer

IMC

Chicago, IL • On-site

$127K - $167K/yr

Other

Posted 14 days ago

Job description

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 you'll 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 - there's no vendor to wait on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the boundaries of what's computationally possible, this role is for you. We're 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

Apply