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JPMorgan Applied AI/ML Lead Vice President United States, California, Palo Alto 874595942
28.01.2025
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
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