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AI Engineer - Equities Portfolio Management - TIAA
AI Engineer
Hands‑on AI Engineer responsible for designing and deploying AI‑driven solutions that improve strategy generation, portfolio rebalancing, trade execution, and advisor tools within an equities portfolio management platform.
About the role
Key Responsibilities
- Identify and prototype AI opportunities—including agentic and generative models—across the equities platform, collaborating with both technical and business stakeholders.
- Own end‑to‑end delivery of multiple AI initiatives, from concept and data collection through model development, testing, deployment, and monitoring.
- Design, train, and fine‑tune machine‑learning and deep‑learning models (e.g., reinforcement learning, time‑series forecasting) that enhance strategy generation and portfolio rebalancing.
- Integrate AI models into production pipelines using cloud services (AWS) and ensure scalability, reliability, and low‑latency inference for trade execution and advisor‑facing tools.
- Implement robust data‑engineering workflows to ingest, clean, and transform large financial datasets for model training and evaluation.
- Mentor junior engineers, share best practices, and contribute to the AI team’s technical roadmap.
Requirements
- 5+ years of professional experience building and deploying machine‑learning or deep‑learning solutions in a production environment.
- Strong proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Hands‑on experience with cloud platforms (AWS) and containerization/orchestration tools (Docker, Kubernetes).
- Solid understanding of financial data, time‑series analysis, and portfolio management concepts.
- Excellent problem‑solving skills and ability to communicate complex AI concepts to non‑technical audiences.
Skills
pythonmachine learningdeep learningawspytorch