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No Experience Machine Learning Jobs in Bolingbrook, IL

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

... on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the ... Trading experience is a bonus, not a prerequisite. Your Core Responsibilities * Architect and co ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the ... Trading experience is a bonus, not a prerequisite. Your Core Responsibilities * Architect and co ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... on and no abstraction layer you're not allowed to touch. If you've ever wanted to push the ... Trading experience is a bonus, not a prerequisite. Your Core Responsibilities * Architect and co ...

Onin Staffing

Machine operator

La Grange, IL

$19.25 - $19.75/hr

... and Experience: Machine Setup: Get machines ready for the daily run. Assemble and take apart ... Run tests to ensure no harmful metals are in the food. Maintenance: Do quick fixes on machines.

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How much do no experience machine learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for no experience machine learning in Bolingbrook, IL is $22.57, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $25.19 per hour, depending on experience, location, and employer.

What kinds of projects or learning opportunities can I expect in a no experience machine learning role?

In a no experience machine learning role, you will often start by assisting with data preprocessing, exploring datasets, and supporting more experienced engineers on real-world projects. You may also participate in internal trainings, mentorship programs, or hands-on workshops to build up your technical skills. Collaboration is common, so expect regular team meetings and opportunities to pair-program or seek guidance from senior colleagues. Over time, as you gain proficiency, you may be assigned small-scale projects or research tasks, providing a clear pathway to take on more complex responsibilities. This supportive environment is designed to help you gradually develop expertise and advance your career in machine learning.

What are the key skills and qualifications needed to thrive in the no experience machine learning position, and why are they important?

To thrive in an entry-level machine learning role with no prior experience, you should possess a solid understanding of mathematics (especially statistics and linear algebra), basic programming knowledge (often in Python), and a willingness to learn. Familiarity with popular data science tools and frameworks such as scikit-learn, TensorFlow, or online courses and certifications in machine learning is advantageous. Curiosity, problem-solving abilities, and effective communication are soft skills that help you work collaboratively and adapt to new challenges. These attributes are important because they enable quick learning, help you contribute to team projects, and support your growth in a rapidly evolving technical field.

What job categories do people searching No Experience Machine Learning jobs in Bolingbrook, IL look for?

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No Experience Machine Learning jobs near you

Hardware Machine Learning Engineer

IMC

Chicago, IL • On-site

$127K - $167K/yr

Full-time

Re-posted 1 hour 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