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Senior Meta Machine Learning Jobs in Naperville, IL

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL

$126K - $166K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Socket.dev

Machine Learning Engineer

Chicago, IL · On-site

About the role Attain is seeking a Senior/Staff Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our suite of B2C financial ...

Meta

Client Solutions Manager

Chicago, IL · Remote

$87K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

Meta

Economic Development Manager

Chicago, IL · On-site

$154K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

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Senior Meta Machine Learning information

See Naperville, IL salary details

$25K

$80.2K

$163.3K

How much do senior meta machine learning jobs pay per year?

As of Sep 15, 2026, the average yearly pay for senior meta machine learning in Naperville, IL is $80,168.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,400.00 and $102,800.00 per year, depending on experience, location, and employer.

What is the difference between Senior Meta Machine Learning vs Data Scientist?

AspectSenior Meta Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, ML, or related fields; experience with meta-learning frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch-focused teams developing advanced ML models, often in AI companiesData analysis, modeling, and visualization across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, e-commerce, tech companies

While both roles involve machine learning expertise, Senior Meta Machine Learning specialists focus on developing advanced meta-learning algorithms, often in research settings, whereas Data Scientists apply data analysis and modeling techniques across diverse industries. The roles share similar educational backgrounds but differ in focus and application.

What are popular job titles related to Senior Meta Machine Learning jobs in Naperville, IL?

For Senior Meta Machine Learning jobs in Naperville, IL, the most frequently searched job titles are:

What job categories do people searching Senior Meta Machine Learning jobs in Naperville, IL look for?

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Cities near Naperville, IL with the most Senior Meta Machine Learning job openings:

Senior Meta Machine Learning jobs near you

Senior Software Engineer (Machine Learning)

Chicago, IL • On-site

Valor Equity Partners
Investment Clubs and Venture Capital Companies • 51 - 200 employees
Learn more about Valor Equity Partnersexternal

$126K - $166K/yr

Full-time

Re-posted 26 days ago

Job description

About Valor:
Valor Equity Partners is a different kind of private investment firm. We pioneered the idea of operational growth. We work side-by-side, shoulder-to-shoulder, to help grow the operations of great companies solving the world's biggest problems. We invest in technology and technology-enabled companies that innovate and disrupt existing industries - from biosciences to transportation to food to health and wellness. We've had the honor of serving some of the world's greatest entrepreneurs and companies, including Tesla, SpaceX, Anduril, Eight Sleep, GoPuff, and others.
Our values are core to all we do. These values are excellence, humility, integrity, and responsibility.
Valor means that we:
  • Strive for excellence in everything we do;
  • Maintain our humility and mutual respect no matter what circumstances we encounter;
  • Insist upon the highest level of integrity in our interactions and in the logic of our investment process; and
  • Demonstrate responsibility and dedication to all of our constituents.

About the Team:
On the Valor Labs Team, we develop cutting edge machine learning models to derive proprietary investment insights and build software applications to augment the Firm's investment decision making process. As a small team of software engineers and data scientists with diverse backgrounds, we work collaboratively on wide-ranging problems to deliver high-impact products for the Firm.
About the Role:
As a Software Engineer on our data science and machine learning team, you will contribute directly to the development of high-impact products. Working together with data scientists, engineers, and stakeholders, you will translate complex project requirements into actionable technical solutions and work collaboratively to build, deploy, monitor, and maintain those solutions in production. Your technical expertise and commitment to excellence will help drive the adoption of best practices and ensure the highest level of rigor in everything we do.
About You:
  • B.S. in Computer Science or related field
  • 5+ years of experience developing production-ready software systems
    • Although not necessary, prior work experience in financial services is highly valued
  • Expertise in end-to-end machine learning operations: model deployment, monitoring, and retraining, supporting integration with production data pipelines and API services.
  • Proficient with Python, especially machine learning libraries like NumPy, Pandas, Scikit-Learn, and PyTorch
  • Proficient with SQL, including transactional (e.g., PostgreSQL) and analytical (e.g., BigQuery) databases
  • Professional experience with most, if not all, of the following:
    • Containerization (e.g., Kubernetes and Docker)
    • Data processing (e.g., Prefect, Airflow, and dbt)
    • Parallel processing (e.g., Ray, Dask, and Spark)
    • Cloud infrastructure (e.g., Google Cloud Platform)
    • Continuous integration/continuous deployment (e.g. GitHub Actions)
    • Infrastructure as code (e.g., Terraform)
    • Tools to support machine learning operations (e.g., MLFlow and DVC)
  • Humble, hard-working, and collaborative

Apply