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Machine Learning Engineer Software Engineer Jobs in Illinois

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Experience optimizing ML models for edge deployment (TensorRT, ONNX, quantization) Software ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... Knowledge of software engineering best practices including version control (Git) and CI/CD ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

TEKsystems is seeking a Machine Learning Engineer to support one of our major customers that sits ... software services, not writing research papers. - Cloud engineering experience is required ...

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end scalable machine learning systems and applications. They use their specialized depth and breadth of ...

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Showing results 21-40

Machine Learning Engineer Software Engineer information

How do machine learning engineer software engineers typically collaborate with data scientists and software development teams?

Machine Learning Engineer Software Engineers often serve as a bridge between data scientists and software development teams. They work closely with data scientists to understand and implement machine learning models, ensuring that the models are production-ready and scalable. Additionally, they collaborate with software engineers to integrate these models into existing applications, monitor their performance, and address any engineering challenges. This cross-functional collaboration is essential for delivering robust, end-to-end AI solutions that add real value to the business.

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

AspectMachine Learning EngineerSoftware Engineer
Required CredentialsBachelor's/Master's in CS, specialized ML coursesBachelor's in CS or related field
Work EnvironmentDevelops ML models, algorithms, data pipelinesBuilds software applications, systems, APIs
Industry UsageAI/ML projects, data-driven solutionsWeb, mobile, enterprise software

Machine Learning Engineers focus on designing and deploying ML models, requiring expertise in algorithms and data handling. Software Engineers develop broader software applications, emphasizing coding and system architecture. While both roles require programming skills, ML Engineers specialize in AI/ML tasks, whereas Software Engineers work across various software domains.

What cities in Illinois are hiring for Machine Learning Engineer Software Engineer jobs?

Cities in Illinois with the most Machine Learning Engineer Software Engineer job openings:

Senior Software Engineer (Machine Learning)

Valor Equity Partners

Chicago, IL • On-site

$126K - $166K/yr

Full-time

Re-posted 19 hours 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