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Machine Learning Engineer Python Jobs in Schaumburg, IL

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 ... Strong object oriented development experience using Python, Java, C# * Familiarity with big data ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... Python and PyTorch and other scientific computing environments a plus Strong mathematical ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

... Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques ... tools such as Python (Scikit-learn, TensorFlow), SQL, Hadoop, and Spark. * Relevant modeling ...

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

... Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques ... tools such as Python (Scikit-learn, TensorFlow), SQL, Hadoop, and Spark. * Relevant modeling ...

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Machine Learning Engineer Python information

See Schaumburg, IL salary details

$22.6K

$137.4K

$198.8K

How much do machine learning engineer python jobs pay per year?

As of Jun 4, 2026, the average yearly pay for machine learning engineer python in Schaumburg, IL is $137,447.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $161,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What are popular job titles related to Machine Learning Engineer Python jobs in Schaumburg, IL? For Machine Learning Engineer Python jobs in Schaumburg, IL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Schaumburg, IL look for? The top searched job categories for Machine Learning Engineer Python jobs in Schaumburg, IL are:
What cities near Schaumburg, IL are hiring for Machine Learning Engineer Python jobs? Cities near Schaumburg, IL with the most Machine Learning Engineer Python job openings:
Senior AI Machine Learning Engineer

Senior AI Machine Learning Engineer

The Hartford Financial Services Group, Inc.

Chicago, IL • On-site, Remote

$107K - $147K/yr

Full-time

Posted 27 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

52nd of 260 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 industry-leading 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 production-grade 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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