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Staff Software Engineer Machine Learning Jobs in Hammond, IN

You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Staff Software Engineers are leading experts in their domains, helping ...

... approaching software engineering and/or machine learning problems Essential Job Functions ... staffing agency, recruiting service, sourcing entity or any other third-party paid service at any ...

... approaching software engineering and/or machine learning problems Essential Job Functions ... staffing agency, recruiting service, sourcing entity or any other third-party paid service at any ...

Staff Software Engineer - IE07IE We're determined to make a difference and are proud to be an ... learning and improvement. * Drive best practices in software development, including coding ...

Staff Software Engineer

Chicago, IL · Hybrid

$116K - $174K/yr

Staff Software Engineer - IE07IE We're determined to make a difference and are proud to be an ... learning and improvement. * Drive best practices in software development, including coding ...

Staff Software Engineer CI/CD As a Staff Engineer at Capital One, you will be a part of a community ... You will work alongside our talented team of developers, machine learning experts, product managers ...

SageSure, a leader in catastrophe-exposed property insurance, is seeking a Staff Software Engineer ... We invite you to join our shared commitment to building, shipping, learning, and continuously ...

Staff Software Engineer

Chicago, IL · On-site

$184K - $299K/yr

WHAT YOU'LL DO As a Staff Engineer on Braze's AI Decisioning Experience team, you will play a ... Experience developing user experiences for machine learning and data-intensive applications

About the Role Staff Software Engineer based at John Deere World Headquarters in Chicago leading architecture and implementation of complex, multisystem full‑stack solutions. Drive platform ...

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Staff Software Engineer Machine Learning information

See Hammond, IN salary details

$58.2K

$155.1K

$211.8K

How much do staff software engineer machine learning jobs pay per year?

As of Sep 9, 2026, the average yearly pay for staff software engineer machine learning in Hammond, IN is $155,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,500.00 and $183,400.00 per year, depending on experience, location, and employer.

What are popular job titles related to Staff Software Engineer Machine Learning jobs in Hammond, IN?

For Staff Software Engineer Machine Learning jobs in Hammond, IN, the most frequently searched job titles are:

What job categories do people searching Staff Software Engineer Machine Learning jobs in Hammond, IN look for?

The top searched job categories for Staff Software Engineer Machine Learning jobs in Hammond, IN are:

Infographic showing various Staff Software Engineer Machine Learning job openings in Hammond, IN as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 1% Temporary, and 4% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $155,147 per year, or $74.6 per hour.

Senior Software Engineer (Machine Learning)

Chicago, IL • On-site

Valor Equity Partners
Investment Clubs and Venture Capital Companies • 51 - 200 employees

$126K - $166K/yr

Full-time

Re-posted 21 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