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Machine Learning Engineer Two Jobs in Illinois (NOW HIRING)

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127K - $167K/yr

... 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 ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... 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 ...

Caterpillar

Senior Machine Learning Engineer

Mossville, IL · On-site

$112K - $183K/yr

As a Machine Learning Infrastructure Engineer, you will be responsible for developing and deploying a robust full-stack pipeline that can support various perception/planning/prediction projects. In ...

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IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... 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 ...

Caterpillar Inc.

Senior Machine Learning Engineer

Mossville, IL · On-site

$76K - $104K/yr

The Senior Machine Learning Engineer will develop and deploy a full-stack pipeline for various projects, optimizing efficiency with large data sets and enhancing the safety and efficiency of machines ...

New

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

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Machine Learning Engineer Two information

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning and AI, and often working in high-demand industries or at large tech companies can earn $300,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in competitive markets.

Which 3 jobs will survive AI?

Machine Learning Engineers are likely to continue playing a vital role as AI advances, focusing on developing and refining algorithms. Jobs that require complex problem-solving, creativity, and emotional intelligence—such as healthcare professionals, educators, and skilled tradespeople—are also expected to remain in demand. These roles often involve tasks that are difficult for AI to replicate fully.

What engineer makes $500,000 a year?

A senior or lead machine learning engineer with extensive experience, advanced skills in algorithms and data modeling, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets or top-tier companies.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior machine learning engineers or AI research directors, often in leading tech companies or finance firms. These positions usually require advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership. Compensation at this level reflects significant expertise, responsibility, and impact within the organization.
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Machine Learning Engineer Two jobs near you
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

Apply