Senior Machine Learning Engineer - Digital AI

JPMorgan Chase & Co.; Palo Alto (CA); Sur place; USD 61 000 - 101 000; Plein temps

Résumé du poste

JPMorgan Chase & Co. is seeking a Senior Machine Learning Engineer in Digital Intelligence to lead research and development of next-generation ML architectures for structured and unstructured financial data.

You will prototype pre-training objectives and implement ideas into robust, scalable production systems. The role emphasizes working with multimodal inputs, advanced transformer models, and large-scale compute, while mentoring engineers and collaborating across teams to deliver real-world

Qualifications

• Requires PhD with 2+ years or Master with 4+ years in Computer Science.
• Deep expertise in LLMs, Transformers, attention mechanisms, RoPE, and multimodal inputs.
• Strong PyTorch skills at scale, distributed training with FSDP/DeepSpeed, memory optimization.

Responsabilités

• 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 and translate research advances into deployable systems.
• Optimize training throughput for large data sources.
• Collaborate with other teams to design solutions for product use cases.

Connaissances

LLMs & Transformers

PyTorch & Distributed Training

Foundation Models training

Software engineering for production

Financial data & recommender systems

Publications in AI/ML venues

Serving infrastructure optimization

Post-training LLMs & network optimize

Large-scale compute infrastructure

Real-world product shipping

Formation

PhD in Computer Science

Master's degree in Computer Science

Outils

PyTorch

FSDP

DeepSpeed

Description du poste

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

• We require a PhD with 2+ years of experience, or a Masters degree with 4+ years of experience, in Computer Science, along with training and work experience in Machine Learning, LLM/NLP, or a related field.
• We need deep expertise in LLMs and Transformers, including a strong understanding of attention mechanisms, positional encodings such as RoPE, and the ability to work effectively with multimodal inputs.
• We expect strong PyTorch skills at scale, including hands‑on experience with distributed training tools such as FSDP and DeepSpeed, plus practical memory optimization techniques.
• We look for experience in foundation model training, including pre-training from scratch and designing tokens and vocabularies for complex heterogeneous data such as tabular, temporal, and graph-based formats.
• We need solid software engineering capabilities and the ability to build robust, production-ready systems that operate reliably at scale.
• We require prior experience with financial data and recommendation systems.
• Preferred qualifications include a publication record at top AI/ML venues.
• Preferred qualifications include experience optimizing serving infrastructure.
• Preferred qualifications include experience with post‑training LLMs and network optimization algorithms, as well as interpretability or steering methods for LLMs.
• Preferred qualifications include experience working with large‑scale compute infrastructure.
• Preferred qualifications include experience shipping a real‑world product, project, or feature.

Responsibilities:

• We research and prototype next‑generation architectures for structured and unstructured data.
• We develop novel pre‑training objectives tailored to financial event sequences and heterogeneous profile data.
• We implement research ideas in production‑quality code.
• We mentor engineers on ML best practices and translate research advances into deployable systems.
• We optimize training throughput for large data sources.
• We collaborate with other teams to design solutions for product use cases.

Technologies:

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

More:

We are collaborating with J.P. Morgan to connect with exceptional professionals for this Senior Machine Learning Engineer - Digital Intelligence role within Consumer & Community Banking. Our team serves Chase customers across personal banking, credit cards, mortgages, auto financing, investment advice, small business loans, and payment processing. We are proud to lead the U.S. in credit card sales and deposit growth, offer widely used digital solutions, and rank first in customer satisfaction. In this role, you will work with a high-caliber Digital Intelligence team of software developers and deep learning experts, applying strong technical judgment to select the right approaches, including modern LLM-based methods where appropriate, while helping build reliable, secure, scalable systems and improving data quality, feedback loops, model monitoring, and operational workflows.

last updated 40 week of 2026