1

Machine Learning Testing Jobs in Illinois (NOW HIRING)

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

Senior Machine Learning Test Engineer

Ohio, IL · On-site +1

$104K - $135K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... API Testing * Automate ML QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins)

Agentic AI/AI Engineer - Generative AI & Machine Learning Location:  Schaumburg, IL (Hybrid - 3 ... Familiar with functional and non-functional testing of AI/ML applications and operationalizing it ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

next page

Showing results 1-20

Machine Learning Testing information

See Illinois salary details

$13

$22

$30

How much do machine learning testing jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for machine learning testing in Illinois is $22.11, according to ZipRecruiter salary data. Most workers in this role earn between $19.09 and $24.71 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Testing position, and why are they important?

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

What are the typical challenges faced by professionals in Machine Learning Testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.

What is a Machine Learning Testing job?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

What are the most commonly searched types of Machine Learning Testing jobs in Illinois? The most popular types of Machine Learning Testing jobs in Illinois are:
Infographic showing various Machine Learning Testing job openings in Illinois as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 18% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $45,998 per year, or $22.1 per hour.
Hardware Machine Learning Engineer

Hardware Machine Learning Engineer

IMC

Chicago, IL

$127K - $167K/yr

Other

Re-posted 24 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