Senior ML Engineer - Digital Intelligence & LLMs

Archer; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Comprehensive health care coverage

On-site health and wellness centers

Retirement savings plan

Job summary

Archer partners with JPMorgan Chase to recruit a Senior Machine Learning Engineer-Digital Intelligence for the Chase CCB Data & Analytics initiatives. The role centers on large language models, optimization, interpretability, and related algorithms to turn research into scalable, real-world products in a fast-paced environment.

You will bring a strong software foundation and hands-on zero-to-one ML development experience, with expertise in post-training models, token design, and production-ready

Qualifications

• PhD with 2 years or MS with 4 years in Computer Science, with ML/LLM experience.
• Deep LLM and Transformer expertise with attention mechanisms and multi-modal data handling.
• PyTorch at scale with distributed training (FSDP/DeepSpeed) and memory optimization techniques.
• Experience building production-quality systems and working with financial data or recommendations.

Responsibilities

• Research and prototype next-generation 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 translate research to deployable systems.
• Optimize training throughput for large data sources.
• Collaborate with teams to design solutions for product use cases.

Skills

PhD with ML focus

MS with ML focus

LLM/Transformer expertise

PyTorch at scale

Foundation model training

Software engineering

Finance data experience

Education

PhD in Computer Science

Master's in Computer Science

Tools

FSDP

DeepSpeed

Distributed training

Job description

Archer partners with JPMorgan Chase to recruit a Senior Machine Learning Engineer-Digital Intelligence for the Chase CCB Data & Analytics initiatives. The role centers on large language models, optimization, interpretability, and related algorithms to turn research into scalable, real-world products in a fast-paced environment.

You will bring a strong software foundation and hands-on zero-to-one ML development experience, with expertise in post-training models, token design, and production-ready