1

Machine Learning Engineer Quantization Jobs in Lombard, IL

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126.20K - $166.40K/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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

next page

Showing results 1-20

Machine Learning Engineer Quantization information

See Lombard, IL salary details

$31K

$126.7K

$190.4K

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 Lombard, IL is $126,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $152,500.00 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 Lombard, IL? For Machine Learning Engineer Quantization jobs in Lombard, IL, the most frequently searched job titles are:
What cities near Lombard, IL are hiring for Machine Learning Engineer Quantization jobs? Cities near Lombard, IL with the most Machine Learning Engineer Quantization job openings:
Senior AI Machine Learning Engineer

Senior AI Machine Learning Engineer

The Hartford

Chicago, IL • Hybrid

$126.20K - $166.40K/yr

Full-time

Posted 22 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

53rd of 259 rated insurance


Job description

Sr Data Engineer - GE07BE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

The Hartford seeks a driven, team-focused Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Customer Operations Data Science team.

The Hartford is developing industryleading AI and machine learning capabilities to improve customer experience (CX) at scale. Within Customer Operations Data Science, we build modern AI products that optimize customer interactions across omnichannel journeys, supporting operational areas such as the Contact Center, Premium Audit, and Billing.

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 operations leaders to deliver measurable impact.

Our core values

  • We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design.

  • We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change.

  • We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected.

  • We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving.

  • We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.

Responsibilities

  • Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.

  • Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.

  • Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.

  • Accountable for design, development and maintenance of Models as Service

  • Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.

  • Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams

  • Delivery of critical milestones for model deployment in the AWS and GCP clouds.

  • Adopt and promote MLOps best practices to the Data Science community.

Minimum Requirements

  • Must be authorized to work in the U.S. now and in the future.

  • Master's degree in related field or 5+ years of equivalent experience in a research or DevOps function.

  • Development experience using both the AWS and GCP suite of tools.

  • Familiarity with SageMaker, Streamlit,web security, credentials and API management tools

  • Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.

  • Experience building and deploying webservices in a cloud environment.

  • Experience building CICD pipeline using Jenkins or equivalent

  • Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar

  • Expert-level Github experience, including Github Actions

  • Strong object oriented development experience using Python, Java, C#

  • Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.)and RDBMS platforms such as Redshift, Snowflake or BigQuery

  • Experience in end to end model development lifecycle, from ideation through post production monitoring.

  • Experience with workflow automation platforms (Apache Airflow, Autosys, similar)

  • Experience with Solution Design and Architecture of data pipelines

  • Basic understanding of Data Science model development life cycle

Preferred Skills

  • Fundamentally strong with Data Structures and algorithms.

  • Experience working with Docker, Kubernetes and EC2 environment.

  • Experience building ML and data pipeline and orchestration services

  • Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn,

  • Experience working in an Agile framework.

Qualifications

  • 4+ years of ML engineering, data manipulation and application development

  • 4+ years Python development experience

  • 4+ years working with IAC, developing CICD pipelines

  • 1+ years of experience in the insurance or broader financial services industry

  • 1+ years SQL development experience

  • Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).

Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$117,200 - $175,800

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us|Our Culture|What It's Like to Work Here|Perks & Benefits


What The Hartford employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Hartford logo

About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

Social media