Machine Learning Engineer (Chicago)

Fitch Group • Chicago, IL

5d • $120,000 - $130,000 • Onsite

About The Position

The Fitch Group’s Emerging Technology team is seeking a Machine Learning Engineer to join a team focused on building and supporting Generative AI, Machine Learning (ML), and Data Science solutions across the organization. This position could be based in our Chicago office. The Emerging Technology team objectives include implementing AI & ML technology in collaboration with business partners and product owners, developing and supporting enterprise-level AI exploration tools and capabilities, providing guidance and support for safe development and deployment of AI, and establishing and maintaining policies, guidelines, and processes for AI/ML governance, including third-party AI governance.

Requirements

• 3+ years of experience as a machine learning engineer or in a closely related software engineering role focused on ML systems.
• Experience writing production-quality Python code and applying sound software engineering practices.
• Strong foundation in machine learning concepts and practical experience applying modern ML techniques to real-world problems.
• Strong software engineering fundamentals, including code quality, automated testing, version control, observability, and performance optimization.
• Experience building or integrating Generative AI applications, such as retrieval-augmented generation, evaluation workflows, or agent-assisted systems.
• Experience building or improving search, retrieval, or data access layers that support ML or GenAI applications.
• Experience with containerized deployment and orchestration, such as Docker and Kubernetes.
• Experience with cloud-native ML and data services, especially in AWS. Familiarity with tools such as Bedrock, S3, SageMaker, Azure AI Search, or Azure OpenAI is helpful.
• Bachelor’s degree in computer science, machine learning, data science, applied mathematics, or a related field, or equivalent practical experience.

Nice To Haves

• Passion for using data and ML to drive better business outcomes for customers
• Proven ability to work effectively in a distributed team environment and contribute in fast-paced settings.
• Familiarity with credit ratings agencies, regulations, and data products
• Excellent written and verbal communication skills
• Advocate of good code quality and architectural practices
• Strong interpersonal skills and ability to work proactively as a team player

Responsibilities

• Work closely with product squads and partner teams to design, build, integrate, and deploy ML and GenAI solutions in production, while sharing best practices with other engineers.
• Communicate ML and GenAI concepts clearly to technical and non-technical stakeholders, with a focus on practical application to Fitch use cases.
• Collaborate with engineers, data scientists, and product partners to develop and deploy ML and GenAI solutions that deliver measurable business value.
• Partner with data scientists and domain experts to identify practical opportunities where data, ML, and GenAI can improve business outcomes.
• Build scalable services, pipelines, and workflows for ML and GenAI use cases, with guidance from senior engineers where needed.
• Support production applications by helping maintain reliability, monitoring performance, and using metrics to improve existing ML solutions.
• Use cloud services, primarily in AWS, to support data pipelines, model deployment, and LLM-based workflows. Familiarity with Azure services is a plus.
• Use Python and large-scale workflow orchestration tools (for example, Airflow) to build production-quality services, data pipelines, and integrations across diverse data sources and storage systems.

Benefits

• A high impact role with significant visibility, working on flagship Fitch products
• An excellent opportunity to work in cutting-edge areas of machine learning and data science
• An excellent work culture known for providing a good work-life balance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level