Machine Learning Engineer - Digital Intelligence - Palo Alto

Salary: $61,000 - 101,000 per year Requirements:

• Masters degree with 2+ years of relevant experience, or bachelors degree with 4+ years, in Computer Science; training and work experience in machine learning, LLM/NLP, or a related field.
• Deep expertise in large language models and Transformers, including attention mechanisms, positional encodings such as RoPE, and handling multimodal inputs.
• Proficiency with PyTorch at scale, including distributed training frameworks such as FSDP and DeepSpeed, and practical memory optimization.
• Demonstrated foundation-model training experience, including pretraining from scratch and designing tokens and vocabularies for heterogeneous data such as tabular, temporal, and graphical formats.
• Strong software engineering skills and the ability to build robust, production-quality systems that perform reliably at scale.
• Prior experience with financial data and recommendation systems.
• Preferred: publications at leading AI/ML venues; experience optimizing serving infrastructure, post-training LLMs, network optimization, interpretability or steering techniques, and large-scale compute infrastructure; experience shipping real-world products, projects, or features; rigorous experimentation and ablation design for benchmarking LLM optimizations; strong communication, accountability, collaboration, and work ethic.

• Research and prototype next-generation architectures for structured and unstructured data.
• Develop pretraining objectives tailored to financial event sequences and heterogeneous profile data.
• Turn research ideas into production-quality code and deployable systems.
• Mentor engineers on machine learning best practices and translate research advances into practical solutions.
• Optimize training throughput across large data sources.
• Partner with other teams to design solutions for product use cases.
• Apply sound technical judgment, evaluate performance using rigorous metrics, and deliver reliable, secure, scalable solutions.
• Improve data quality and feedback loops, monitor models in production, and iterate to reduce agent effort and resolution times while improving consistency and quality across operational workflows.

• AI
• Support
• LLM
• Machine Learning
• Model Training
• Network
• PyTorch

More:

We are collaborating with hackajob to connect professionals with J.P. Morgan for a Machine Learning Engineer—Digital Intelligence role in Consumer & Community Banking. You will work with software developers and deep learning experts, focusing on large language modeling, optimization, interpretability, and related algorithms, while bridging research and engineering in a fast-paced, collaborative environment. Our Chase business provides financial services to households and small businesses, and our CCB Data & Analytics team combines disciplines including data governance, strategy, reporting, data science, and machine learning, partnering closely with Technology. We offer competitive total rewards and, for eligible employees, benefits such as health coverage, wellness resources, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We value diversity and inclusion, are an equal opportunity employer, and provide reasonable accommodations. This position is subject to Section 19 of the Federal Deposit Insurance Act; an offer is contingent on review of criminal conviction history, including pretrial diversions or program entries.

last updated 42 week of 2026