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Associate Applied Researcher - Agentic AI Systems - JPMorganChase
Software Engineer
Associate Applied Researcher building end‑to‑end agentic AI systems for quantitative trading, turning cutting‑edge GenAI models into production‑ready workflows that handle client requests with high reliability and speed.
About the role
Key Responsibilities
- Design, prototype, and productionize multi‑step LLM agents that automate inbound client request handling.
- Integrate frontier generative AI models into existing quantitative trading infrastructure.
- Develop robust pipelines for data ingestion, model fine‑tuning, and real‑time inference.
- Collaborate with research, engineering, and trading teams to translate research breakthroughs into production‑grade solutions.
- Monitor, evaluate, and continuously improve system performance, reliability, and latency in a live trading environment.
Requirements
- Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow).
- Hands‑on experience building, fine‑tuning, and deploying Large Language Models or other generative AI technologies.
- Proficiency in cloud platforms (AWS, GCP, or Azure) and container orchestration for scalable deployments.
- Solid understanding of prompt engineering, LLM agent architectures, and reinforcement learning concepts.
- Ability to thrive in ambiguous, fast‑paced environments and deliver production‑ready code quickly.