ML Engineer, Digital Intelligence (LLM/AI)

JPMorgan Chase & Co.; Palo Alto (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an ML Engineer-Digital Intelligence in the Consumer & Community Banking division. You will apply strong technical judgment to build reliable, secure, and scalable ML solutions, focusing on large language models and modern deep learning techniques.

You will work with a team of software engineers and ML experts to turn research into real-world products. The role emphasizes zero-to-one ML development, post-training ML, and collaboration across teams in a fast-paced

Qualifications

• Master’s degree with 2+ years or Bachelor's with 4+ years in CS with ML/LLM experience.
• Deep LLM and Transformer expertise — attention mechanisms, RoPE, and multi-modal data handling.

Responsibilities

• Research and prototype next-generation architectures for structured and unstructured data.
• Develop novel pre-training objectives for financial event sequences and heterogeneous profile data.
• Implement research ideas in production-quality code.
• Mentor engineers on ML best practices; translate research advances into deployable systems.
• Optimize training throughput for large data sources.
• Collaborate with other teams to design solutions for product use cases.

Skills

LLM/NLP

Transformer models

PyTorch

Distributed training

Memory optimization

Software engineering

Financial data

Recommendation systems

Education

Master’s degree in CS

Bachelor’s degree in CS

Tools

FSDP

DeepSpeed

RoPE

Tokenization design

Job description

JPMorgan Chase & Co. is seeking an ML Engineer-Digital Intelligence in the Consumer & Community Banking division. You will apply strong technical judgment to build reliable, secure, and scalable ML solutions, focusing on large language models and modern deep learning techniques.

You will work with a team of software engineers and ML experts to turn research into real-world products. The role emphasizes zero-to-one ML development, post-training ML, and collaboration across teams in a fast-paced