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# Machine Learning Engineer - Digital Intelligence

- **Company:** JPMorgan Chase & Co.
- **Location:** Palo Alto, CA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Code Optimization, Encodings, Distributed Computing Environment, Machine Learning, Recommender Systems, Software Engineering, Unstructured Data, Pytorch, DeepSpeed, Large Language Models, Attention Mechanisms, Information Technology, Network Optimization
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25197_cc8abe3eeabda3633917b814c3842389

## About the Role

* 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, positional encodings such as RoPE, and the ability to handle multi-modal data inputs effectively.
 * PyTorch proficiency at scale - hands-on experience with distributed training frameworks including FSDP and DeepSpeed, alongside practical memory optimization techniques.
 * Foundation model training - proven experience in pre-training from scratch and designing tokens and vocabularies for complex, heterogeneous data sources including tabular, temporal, and graphical formats.
 * Strong software engineering skills - ability to build robust, production-quality systems that perform reliably at scale.
 * Prior experience with financial data and recommendation systems., * Publication record at top AI/ML venues.
 * Experience optimizing serving infrastructure is a plus.
 * Experience with post-training LLMs and network optimization algorithms, as well as interpretability or steering techniques for LLMs.
 * Experience working with large-scale compute infrastructure.
 * Experience shipping a real-world product, project, or feature.
 * Experimental rigor and ablation design when benchmarking LLM optimizations.
 * Strong communication and accountability skills, with a collaborative mindset and strong work ethic.

## Description

* Research and prototype next-generation architectures for structured and unstructured data
 * Develop novel pre-training objectives tailored to 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.