About this role
Fitch Ratings seeks a Machine Learning Engineer for its AI Innovation teams in Chicago. This senior individual contributor will remain hands-on while shaping the architecture and engineering standards for AI systems used in financial and credit analysis. The role has no direct people-management responsibilities and is marked as hybrid.
Responsibilities
- Architect and build production machine-learning systems, generative AI platforms, agentic workflows and intelligent automation for analysts and financial professionals.
- Explore LLMs, multi-agent systems, RAG, model fine-tuning and prompt engineering; develop proofs of concept, assess emerging approaches and bring promising capabilities into production.
- Set ML architecture, technology choices, engineering practices and AI governance patterns. Build scalable model-deployment APIs and ML CI/CD pipelines; monitor SLAs, model performance and reliability.
- Mentor engineers and collaborate with product squads, business stakeholders and distributed teams, communicating technical decisions to both technical and non-technical audiences.
Required qualifications
- 12+ years of professional experience building production AI/ML systems; strong Python skills, knowledge of classical and deep-learning algorithms, and experience delivering advanced generative AI and ML solutions.
- Experience designing scalable ML systems from scratch; hands-on work with LLMs, agentic systems, RAG and neural-network training or fine-tuning using frameworks such as PyTorch.
- Production ML engineering experience with containerization, Docker, Kubernetes or AWS EKS, AWS or Azure, Airflow, automated testing and deployment APIs. Demonstrated technical leadership, mentoring, experimentation and cross-functional communication.
- Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics or a related field.
Preferred qualifications include taking AI research or prototypes into production; ML thought leadership or open-source contributions; advanced multi-agent systems; cloud-native ML infrastructure and cost-efficient LLM deployment; financial services, credit analysis or ratings-agency knowledge; greenfield product experience; and participation in Toronto's AI/ML community.
For Chicago roles, expected base pay is 140,000–180,000 USD, determined individually. Depending on the position, total compensation may also include bonuses, long-term incentives or other benefits. The posting describes access to compute and research resources, conference and training budgets, and opportunities to advance into senior AI technical roles.