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Machine Learning Engineer Quantization Jobs in Chicago, IL

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Role description AWS Machine Learning Engineer ML Engineer I Who We Are: Born digital, UST transforms lives through the power of technology. We walk alongside our clients and partners, embedding ...

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 ...

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 ...

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 ...

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

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

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 ...

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

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

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Machine Learning Engineer Quantization information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

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 Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 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 job categories do people searching Machine Learning Engineer Quantization jobs in Chicago, IL look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Machine Learning Engineer Quantization jobs? Cities near Chicago, IL with the most Machine Learning Engineer Quantization job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Allied Benefit Systems

Chicago, IL • Remote

$126K - $166K/yr

Full-time

Medical, Dental, Vision, Life, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


Allied Benefit Systems rating

8.1

Company rating: 8.1 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

86th of 428 rated business services


Job description

POSITION SUMMARY

The Senior Machine Learning Engineer is responsible for designing, building, and deploying scalable machine learning systems that drive business impact. This role will partner closely with data scientists, AI Technical Product Owners, and engineering teams to integrate machine learning capabilities into real business processes. The emphasis is on operational excellence, scalability, and long-term maintainability rather than research and experimentation.

ESSENTIAL FUNCTIONS

  • Design and implement end to end machine learning pipelines that support data ingestion, feature generation, model training, validation, deployment, and monitoring.
  • Operationalize models in coordination with data scientists and ensure they run reliably with requisite alerts and monitoring in production environments.
  • Build reusable frameworks and patterns that reduce friction when deploying new models or updating existing ones.
  • Ensure pipelines are secure, auditable, and appropriate for use in regulated enterprise environments.
  • Own and evolve the MLOps toolchain that supports model versioning, artifact management, experiment tracking, and deployment workflows.
  • Implement continuous integration and deployment practices for machine learning systems.
  • Establish monitoring and alerting for model performance, data quality, drift, and system health.
  • Partner with cloud and platform teams to manage compute resources, cost controls, and environment configurations.
  • Work with application engineering teams to integrate machine learning outputs into downstream systems and user workflows.
  • Support real time and batch inference patterns depending on business needs.
  • Ensure that machine learning services meet performance, reliability, and availability expectations for production use.
  • Collaborate closely with data scientists to shape models that are production ready and operationally sustainable.
  • Provide guidance on feature engineering, model packaging, and performance tradeoffs from a deployment perspective.
  • Document standards, patterns, and best practices for building and operating machine learning systems.
  • Contribute to the maturation of the organization's overall AI and ML engineering discipline.
  • Other duties as assigned

EDUCATION

  • Bachelor's degree in Computer Science, Math, Statistics, or equivalent work experiencerequired.

EXPERIENCE AND SKILLS:

  • 6+ years of strong experience building and operating machine learning systems in production environments.
  • Solid software engineering skills with Python and familiarity with modern ML frameworks such as PyTorch or TensorFlow.
  • Experience with data pipelines, workflow orchestration, and model deployment patterns.
  • Hands on experience with cloud platforms and managed ML services, with Azure, AWS, and/or Databricks experience preferred.
  • Understanding of MLOps concepts including model versioning, monitoring, testing, and lifecycle management.
  • Experience working with sensitive data in regulated industries such as healthcare or insurance is strongly preferred.
  • Ability to work cross functionally and translate between data science, engineering, and business stakeholders.

POSITION COMPETENCIES

  • Accountability
  • Analytical Problem Solving
  • Collaboration
  • Execution and Delivery
  • Quality and Risk Management
  • Systems Thinking
  • Technical/Functional Expertise

PHYSICAL DEMANDS

  • This is a standard desk role requiring extended sitting and computer work

WORK ENVIRONMENT

  • Remote

Here at Allied, we believe that great talent can thrive from anywhere. Our remote friendly culture offers flexibility and the comfort of working from home, while also ensuring you are set up for success. To support a smooth and efficient remote work experience, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 100Mbps download/25Mbps upload. Reliable internet service is essential for staying connected and productive.

The company has reviewed this job description to ensure that essential functions and basic duties have been included. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills, and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate.

Compensation is not limited to base salary. Allied values our Total Rewards, and offers a competitive Benefit Package including, but not limited to, Medical, Dental, Vision, Life and Disability Insurance, Generous Paid Time Off, Tuition Reimbursement, EAP, and a Technology Stipend.

Allied reserves the right to amend, change, alter, and revise, pay ranges and benefits offerings at any time. All applicants acknowledge that by applying to the position you understand that the specific pay range is contingent upon meeting the qualification and requirements of the role, and for the successful completion of the interview selection and process. It is at the Company's discretion to determine what pay is provided to a candidate within the range associated with the role.