Senior Machine Learning Engineer
MorningstarResponsibilities
- Design and develop scalable AI-driven data collection and enrichment workflows for structured and unstructured data.
- Build LLM-based capabilities including RAG, prompt orchestration, entity extraction, summarization, classification, and automated validation.
- Implement agentic workflows and model-to-tool integrations connecting models with internal tools, APIs, knowledge stores, data sources, and workflow systems.
- Deploy, maintain, optimize, version, evaluate, and monitor ML and LLM models in production.
- Build evaluation frameworks for extraction quality, model performance, hallucination risk, grounding, consistency, latency, coverage, and data reliability.
- Implement observability capabilities including monitoring, logging, tracing, alerting, cost tracking, drift detection, and reliability dashboards.
- Design distributed, event-driven, cloud-native systems for high-volume workloads using asynchronous processing, message queues, containerization, and orchestration.
- Evaluate emerging AI/ML technologies, LLM frameworks, orchestration tools, vector databases, and model deployment approaches.
- Mentor engineers and promote strong engineering practices across the team.
- Collaborate with ML engineers, product managers, researchers, business stakeholders, and global teams.
Requirements
- Bachelor’s or master’s degree in Computer Science, Data Science, Mathematics, or a related technical field.
- 5+ years of experience in machine learning engineering or data science focused on machine learning systems, ML platforms, or distributed systems.
- Strong experience building production-grade ML systems, including model deployment and lifecycle management.
- Hands-on experience with MLOps practices and tools, including CI/CD, model monitoring, and experiment tracking.
- Strong programming skills in Python and SQL, or similar languages.
- Experience with cloud platforms and containerization, including AWS, GCP, Azure, Docker, or Kubernetes.
- Production experience with LLM-based systems, including RAG pipelines, embeddings, and vector databases.
- Solid understanding of distributed systems, scalability, and system design trade-offs.
- Proven ability to solve complex technical challenges and deliver scalable solutions.
- Excellent communication and collaboration skills, including experience working across global teams.
- Experience working in fast-paced, data-driven environments.
Benefits
- Hybrid work environment with four days in the office each week in most locations.
- Additional benefits are available to support flexibility as needs change.
- Standard office setting with limited corporate travel potentially required for remote offices, business meetings, and events.
Categories
About Morningstar
Morningstar, Inc. is a leading provider of independent investment insights in North America, Europe, Australia, and Asia. The Company offers an extensive line of products and services for individual investors, financial advisors, asset managers and owners, retirement plan providers and sponsors, institutional investors in the debt and private capital markets, and alliances and redistributors. Morningstar provides data and research insights on a wide range of investment offerings, including managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. Morningstar also offers investment management services through its investment advisory subsidiaries, with approximately $369 billion in AUMA as of Sept. 30, 2025. The Company operates through wholly-owned subsidiaries in 32 countries.