Principal Research Engineer, AI/ML

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Jersey City, NJ
Posted
9 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $221k
$169k most similar roles pay here $277k

This listing doesn't post a salary. Most similar roles pay $187,437–$254,750.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Principal Research Engineer, AI/ML

As a Principal Research Engineer - AI/ML on the Applied Artificial Intelligence and Machine Learning team, you will lead the design and delivery of agent-based and generative artificial intelligence solutions to transform complex operations. You will architect end-to-end systems that automate workflows, translate ambiguous business problems into research hypotheses, and build collaborating agents for multi-step processes. Your daily work involves designing reusable services, evaluation frameworks, and robust experimentation practices while mentoring engineers through technical guidance. The role requires expertise in machine learning fundamentals, distributed systems for model training and inference, and experience with large language models or reinforcement learning. You will utilize tools like Amazon SageMaker, Amazon Bedrock, and Kubernetes-based platforms to solve operational challenges within the financial services sector, ensuring all production-ready designs meet strict requirements for reliability, security, and maintainability in a regulated environment.

What you'll do

  • Architect end-to-end agent-based and generative AI solutions to automate complex operational workflows.
  • Translate ambiguous business problems into research hypotheses, measurable success metrics, and production-ready designs.
  • Build and ship multiple collaborating agents that coordinate planning and execution across multi-step processes.
  • Design reusable services, libraries, and evaluation frameworks to accelerate adoption across engineering teams.
  • Establish robust experimentation practices including offline/online evaluation, monitoring, and iterative improvement loops.
  • Ensure AI solutions meet enterprise standards for reliability, security, and long-term maintainability in production.
  • Mentor and coach engineers and researchers through design reviews and technical guidance.

What we're looking for

  • Formal training or certification in applied AI and machine learning concepts.
  • 10+ years of experience in applied artificial intelligence and machine learning.
  • Master’s or doctorate degree in computer science, engineering, statistics, or a related quantitative field.
  • Experience deploying machine learning and generative AI systems into production at enterprise scale.
  • Strong foundation in machine learning fundamentals, experimental design, and data-driven decision-making.
  • Experience designing distributed systems for model training, inference, and stateful services in production environments.
  • Proven ability to create evaluation strategies for agent-based systems regarding quality, safety, latency, cost, and reliability.
  • Strong programming skills with a track record of building maintainable, reusable components.

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