ML Engineer, Digital Intelligence — LLMs & Production

JPMorganChase; Palo Alto (CA); On-site; USD 130,000 - 210,000; Full time

Job summary

JPMorganChase in Palo Alto is seeking a Machine Learning Engineer specializing in digital intelligence to advance large language model systems. You will translate research into scalable production code and collaborate with a team of engineers and ML experts.

The role emphasizes building reliable, secure AI services, optimizing training, handling multi-modal data, and applying rigorous metrics to improve performance in real-world banking applications.

Qualifications

• Master's degree with 2+ years or Bachelor's with 4+ years in Computer Science, with training and work experience in Machine Learning, LLM/NLP or similar fields.
• Deep LLM and Transformer expertise — strong command of attention mechanisms, RoPE, and multi-modal data inputs.
• PyTorch proficiency at scale — distributed training with FSDP/DeepSpeed, memory optimization.
• Foundation model training — pre-training from scratch and token/vocabulary design for heterogeneous data (tabular, temporal, graphical).
• Strong software engineering skills; production-quality systems that scale.

Responsibilities

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

Skills

LLM/NLP

Transformer architectures

Distributed training

Post-training LLMs

Memory optimization

Multi-modal data handling

Education

Master's degree in Computer Science

Bachelor's degree in Computer Science

Tools

PyTorch

DeepSpeed

FSDP

Job description

JPMorganChase in Palo Alto is seeking a Machine Learning Engineer specializing in digital intelligence to advance large language model systems. You will translate research into scalable production code and collaborate with a team of engineers and ML experts.

The role emphasizes building reliable, secure AI services, optimizing training, handling multi-modal data, and applying rigorous metrics to improve performance in real-world banking applications.