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Machine Learning Engineer Quantization Jobs in Naperville, IL

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127.20K - $167.90K/yr

We're looking for researchers and experienced engineers from any background. Trading experience is ... search, machine learning systems and quantization methods, and determine what translates to ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... search, machine learning systems and quantization methods, and determine what translates to ... engineers, traders, and business operations professionals are united by our uniquely collaborative ...

Darwill, Inc.

Machine Learning Engineer

Villa Park, IL · On-site

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of ...

Ontrac Solutions

Machine Learning Engineer

Chicago, IL · On-site

$70 - $90/hr

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation engagement for one of our clients. This role is ideal for junior-to-mid-level engineers with strong ...

Ontrac Solutions

Machine Learning Engineer

Chicago, IL

$70 - $90/hr

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation engagement for one of our clients. This role is ideal for junior-to-mid-level engineers with strong ...

IMC

Machine Learning Engineer

Chicago, IL · On-site

$175K - $250K/yr

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with ...

Coinflow

Machine Learning Engineer

Chicago, IL · On-site

$160K - $220K/yr

Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers our platform. This is a zero-to-one role. You will be the first dedicated ML hire and will own how ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Capital One

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$107.60K - $147.80K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users. As a Senior ...

PayPal, Inc.

Machine Learning Engineer

Chicago, IL · On-site

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

PayPal

Machine Learning Engineer

Chicago, IL

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Naperville, IL

Machine Learning Engineer Quantization information

See Naperville, IL salary details

$31.5K

$128.6K

$193.2K

How much do machine learning engineer quantization jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning engineer quantization in Naperville, IL is $128,577.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,300.00 and $154,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What are popular job titles related to Machine Learning Engineer Quantization jobs in Naperville, IL? For Machine Learning Engineer Quantization jobs in Naperville, IL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Naperville, IL look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Naperville, IL are:
What cities near Naperville, IL are hiring for Machine Learning Engineer Quantization jobs? Cities near Naperville, IL with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Naperville, IL as of May 2026, with employment types broken down into 1% Internship, 55% Full Time, 40% Part Time, 1% Temporary, 1% Contract, and 2% Nights. Highlights an 84% Physical, 8% Hybrid, and 8% Remote job distribution, with an average salary of $128,577 per year, or $61.8 per hour.

Hardware Machine Learning Engineer

IMC

Chicago, IL

$127.20K - $167.90K/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

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