As a Senior Lead Applied AI/ML Data Scientist at JPMorgan Chase within the Engineer's Platform & Integrated Experience (EPIX) organization, you are an integral part of an agile team (AI Experiments) that works to enhance, build, and deliver trusted market-leading Generative AI products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

The Engineer's Platform & Integrated Experience EPiX group at JPMorgan Chase aims to simplify and accelerate software development by building a unified platform that is Secure, Reliable, Integrated and Accelerates Delivery, powered by AI to make JPMC the most attractive engineering destination for engineers. In this role you will dsign and deliver innovative, high business value Generative AI solutions using state of the art LLMs, RAG, and Agents.

Job responsibilities Fine tune LLM models for improved performance in summarization, Q&A, tool calling, and code generation. Design and implement Retrieval Augmented Generation (RAG) systems and pipelines Design, monitor and interpret Generative AI benchmarking systems to advance the firm's understanding of various LLM and Agentic system capabilities Develop prompts and prompt engineering strategies to enable LLMs to achieve capability for complex task comprehension and execution Create and continously improve graph-indexed knowledge bases for accurate retrieval for LLM augmentation Evaluate and integrate state-of-the-art Generative AI techniques/products for information retrieval, agentic workflows, and LLM fine tuning Lead, mentor and guide other team members on cutting edge AI/ML techniques in Generative AI domain Lead projects through 0-1 innovation cycle collaborating with engineers, product teams and Customers. Adds to the team culture of diversity, equity, inclusion, and respect. Required qualifications, capabilities, and skills 4+ years of applied AI/ML data science or research experience and BS/MS/PhD degree in engineering or quantitative discipline Strong fundamental AI knowledge in tokenization, embeddings, transformer architecture, optimization, information retrieval, prompt engineering Experience with NLP projects using prompt engineering, prompt based learning, Chain-Of-Thought techniques. Experience with LLM fine tuning techniques: SFT, RLHF, DPO, Lora, Quantization Experience with Generative AI frameworks such as LangChain, LlamaIndex, Ray, and PyTorch Distributed fine tuning of pre-trained LLMs with Ray DeepSpeed, or Megatron-LM Strong experience in one or more programming language(s): Python, Go, Java, Javascript Knowledge of Software Design Life Cycle processes, CI/CD, Git, CVE patching. Preferred Qualifications Practical cloud Infrastructure experience