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Machine Learning Engineer Quantization Jobs in Naperville, IL

IMC

Principal Machine Learning Engineer

Chicago, IL · On-site

$200K - $250K/yr

We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll ...

IMC

Principal Machine Learning Engineer

Chicago, IL · On-site

$200K - $250K/yr

We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll ...

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

Inference optimization (quantization, speculative decoding, vLLM, Triton) * Experience shipping LLM ... Equipment and learning budget to help you do your best work and keep up with the frontier

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

Inference optimization (quantization, speculative decoding, vLLM, Triton) * Experience shipping LLM ... Equipment and learning budget to help you do your best work and keep up with the frontier

The Hartford

AI Machine Learning Engineer

Chicago, IL · Hybrid

$100K - $151K/yr

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

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

Inference optimization (quantization, speculative decoding, vLLM, Triton) * Experience shipping LLM ... Equipment and learning budget to help you do your best work and keep up with the frontier

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL

$126K - $166K/yr

Inference optimization (quantization, speculative decoding, vLLM, Triton) * Experience shipping LLM ... Equipment and learning budget to help you do your best work and keep up with the frontier

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126K - $166K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and operationalizing productiongrade AI solutions-partnering closely with product, engineering, and ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

PayPal

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

Huxley

Senior Machine Learning Engineer

Chicago, IL · On-site

$107K - $147K/yr

Our client is looking to bring on a Senior Machine Learning Engineer to help build and scale a nextgeneration voice-centric AI platform used by millions. In this role, you'll own the full ML ...

PayPal, Inc.

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

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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 Jun 20, 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 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 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 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

Principal Machine Learning Engineer

IMC

Chicago, IL • On-site

$200K - $250K/yr

Full-time

PTO

Posted 12 days ago

Job description

At IMC, we believe technology is the foundation of our competitive edge - and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. Now we're expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll work alongside researchers and technologists to design the systems that power experimentation, training, and deployment of ML models - and help set the direction for how machine learning is done at IMC as we scale. If you've built ML infrastructure at scale elsewhere and are looking for a role where your ideas will genuinely help shape our firm's future - we'd love to hear from you.
Your Core Responsibilities:
  • Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster
  • Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines
  • Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading
  • Work with researchers to adapt and deploy modern architectures - transformers, state-space models, temporal convolutions, graph neural networks - to noisy, high-frequency financial data. Explore techniques like self-supervised pretraining, representation learning, and cross-sectional modelling where they offer genuine edge
  • Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment
  • Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work
  • Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work - whether that's new architectures, training techniques, or tooling

Your Skills and Experience:
  • 8+ years of experience building ML platforms or infrastructure at a leading tech company, research lab, or quantitative firm
  • A track record of designing and owning large-scale training and inference systems - not just contributing, but architecting
  • Deep proficiency in Python, with strong experience in either CUDA or C++
  • Hands-on expertise with modern deep learning frameworks (PyTorch, TensorFlow, or JAX) and practical experience implementing architectures like transformers, attention mechanisms, or sequence models
  • Strong foundation in deep learning fundamentals: optimization, regularization, loss design, and the trade-offs that matter when training at scale
  • Experience with distributed training at scale (Horovod, NCCL) and GPU optimization (cuDNN, TensorRT)
  • History of deploying models to production with strong observability, reproducibility, and monitoring practices
  • Comfort working across the ML stack from data pipelines to training infrastructure to serving systems

Why This Role:
  • Build, don't inherit - You'll make foundational technology choices in a platform that's still being defined, not maintain someone else's legacy.
  • Real investment, real backing - This is a strategic priority with resources behind it, not a side experiment.
  • Direct impact on trading - Your infrastructure will power models that make real trading decisions in competitive global markets.
  • Global scope - Work with teams across New York, Chicago, Amsterdam, London, Sydney, Hong Kong and beyond; define practices that can scale worldwide.
  • Ideas over titles - IMC's culture values clarity, rigor, and collaboration. The best ideas win, regardless of where they come from.
  • Tight coupling with research - You won't be building in isolation. Researchers and engineers work side-by-side, iterating together.

#LI-DNP
The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.
Salary Range
$200,000-$250,000 USD
About Us
IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

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