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Machine Learning Engineer Jobs in Bartlett, IL (NOW HIRING)

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 ...

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

... 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 ...

... 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 ...

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 ...

... 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 ...

Sr Machine Learning Engineer

Chicago, IL

$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 ...

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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Showing results 1-20

Machine Learning Engineer information

See Bartlett, IL salary details

$31.2K

$127.4K

$191.4K

How much do machine learning engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for machine learning engineer in Bartlett, IL is $127,352.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Machine Learning Engineer jobs in Bartlett, IL look for? The top searched job categories for Machine Learning Engineer jobs in Bartlett, IL are:
What cities near Bartlett, IL are hiring for Machine Learning Engineer jobs? Cities near Bartlett, IL with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Bartlett, IL as of July 2026, with employment types broken down into 86% Full Time, 2% Part Time, 2% Contract, and 10% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $127,352 per year, or $61.2 per hour.
Senior AI Machine Learning Engineer

Senior AI Machine Learning Engineer

The Hartford

Chicago, IL • Hybrid

$126K - $166K/yr

Full-time

Re-posted 9 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 111 frontline employees who took The Breakroom Quiz

54th of 281 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

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