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Machine Learning Engineer Quantization Jobs in Naperville, IL

Synergistic it

AI & Machine Learning Engineer

Chicago, IL

$118K - $141.80K/yr

... machine learning/AI engineer . In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on ...

Synergistic it

AI & Machine Learning Engineer

Chicago, IL

$118K - $141.80K/yr

... machine learning/AI engineer . In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · On-site

$117.20K - $175.80K/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 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.

AI & Machine Learning Engineer

Synergistic it

Chicago, IL

$118K - $141.80K/yr

Other

Posted 25 days ago

Job description

Job Search Feeling Like Guesswork? Applied to 200+ Jobs and Still No Interviews? Applied Everywhere?

Still No Interviews or Offers? Get Hired with a Process! Many job seekers assume the tech market has shut down, but the truth is companies are still hiring — they’re just being more selective.

That means only the most prepared, polished, and employer‑ready candidates get through.If you’ve sent out hundreds—maybe thousands—of applications and your inbox is still silent, it doesn’t mean you’re not capable. It usually means your profile isn’t lining up with how companies filter, shortlist, and interview candidates right now. In today’s market, employers expect more than a degree or a few tutorial projects.

They want candidates who look job-ready on paper , sound confident in interviews , and demonstrate hands-on ability in the tools teams actually use. That’s exactly what SynergisticIT solves—because the real challenge isn’t learning in isolation. The real challenge is translating learning into interviews and offers .

Since 2010 , SynergisticIT has helped thousands of candidates secure full-time roles with leading companies and recognizable brands—think Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Intel, Walmart Labs, Citi, JPMC, Bank of America, Wayfair , and many more—often in the $95k to $154k offer range depending on role, location, and skillset. The purpose of SynergisticIT is simple: close the gap between what you know and what employers expect you to prove . Here’s the truth employers hire based on whether you can handle real work—clean coding, debugging, teamwork workflows, version control, APIs, cloud basics, deployment pipelines, and the ability to explain what you did.

That’s why SynergisticIT emphasizes structured skill-building, project depth, resume positioning, interview readiness, and support through the job-search process. What roles are in demand right now? A lot of jobseekers assume they must become “AI experts” overnight.

Not true. Many companies are actively hiring professionals in core roles that run modern software teams. In JOPP, the demand typically includes roles such as entry-level software programmer , Java full stack developer , Python/Java developer , data analyst , data engineer , data scientist , and machine learning/AI engineer .

In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on what employers repeatedly request. Who benefits most from this model? If you’re applying and not seeing results, you’re likely in one of these situations: You have skills, but your resume doesn’t show impact and your projects look generic You know tools, but you can’t explain them confidently in interviews You’ve learned from courses, but you lack real-world structure and job alignment You’ve built a portfolio, but it doesn’t match what hiring managers evaluate SynergisticIT works especially well for candidates such as: recent grads in CS/Engineering/Math/Stats , jobseekers who were laid off and need an updated stack, career switchers who want a guided plan, candidates with career gaps , people with “learning but not hired” bootcamp history, experienced professionals not landing interviews, and international candidates on F1/OPT needing a clear employment pathway.

SynergisticIT also supports candidates with guidance around STEM extension , and provides process support for H-1B and Green Card filing once employed (as applicable through employers and standard processes). If you want to explore here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Discover JOPP: Job Placement Program Contact Us https://www.synergisticit.com/contact-us/ You don’t need more random applications. You need a job-ready plan.

Start smarter—start with the right support. Please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT What Recruiters Look for in Junior Developers | SynergisticIT Software engineering or Data Science as a career? Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req.

Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don’t want to be contacted please don’t submit your resume. A lot of jobseekers assume they must become “AI experts” overnight.

Not true. Many companies are actively hiring professionals in core roles that run modern software teams. In JOPP, the demand typically includes roles such as entry-level software programmer , Java full stack developer , Python/Java developer , data analyst , data engineer , data scientist , and machine learning/AI engineer .

In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on what employers repeatedly request. Who benefits most from this model? If you’re applying and not seeing results, you’re likely in one of these situations: You have skills, but your resume doesn’t show impact and your projects look generic You know tools, but you can’t explain them confidently in interviews You’ve learned from courses, but you lack real-world structure and job alignment You’ve built a portfolio, but it doesn’t match what hiring managers evaluate SynergisticIT works especially well for candidates such as: recent grads in CS/Engineering/Math/Stats , jobseekers who were laid off and need an updated stack, career switchers who want a guided plan, candidates with career gaps , people with “learning but not hired” bootcamp history, experienced professionals not landing interviews, and international candidates on F1/OPT needing a clear employment pathway.

SynergisticIT also supports candidates with guidance around STEM extension , and provides process support for H-1B and Green Card filing once employed (as applicable through employers and standard processes). If you want to explore here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Discover JOPP: Job Placement Program Contact Us https://www.synergisticit.com/contact-us/

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