Lead Applied AI Research Scientist

• Advance applied research across the LLM stack, including model training, adaptation, inference, and agentic systems.
• Design, build, and release foundation-model and agentic systems that support high-value business workflows from prototype to production.
• Develop methods to evaluate, verify, and monitor models and agents, including faithfulness, hallucination detection, and workflow verification.
• Enhance research capabilities in model explainability, reliability, and interpretability.
• Provide innovative research solutions to internal project teams.
• Collaborate with researchers to document findings in scientific papers and present at conferences.
• Contribute to intellectual property by pursuing necessary protections for generated IP.
• Work with cross-functional teams to integrate AI solutions into business processes.
• Present research outcomes to stakeholders and at industry conferences.
• Stay current with advancements in AI and machine learning.
• Foster a culture of innovation and continuous improvement within the team.

• Ph.D. in computer science, machine learning, or related fields, plus at least 2 years of experience (industry or postdoc), or a Master's degree with equivalent applied research and engineering experience plus 4 years of industry experience.
• Ability to build and ship AI/ML systems, ideally involving LLMs.
• Proficiency in Python and modern ML frameworks such as PyTorch or JAX.
• Hands-on experience across the LLM lifecycle, including fine-tuning, prompting, serving, and evaluation.
• Experience in scientific technical writing.
• Strong communication skills and ability to present findings to a non-technical audience.
• Experience in model training and adaptation (e.g., supervised fine-tuning, RLHF, preference optimization, distillation, parameter-efficient methods).
• Experience in inference and serving (e.g., test-time compute, speculative decoding, quantization, KV-cache management).
• Experience in agentic systems (e.g., planning, tool and function calling, retrieval-augmented generation, orchestration).
• Experience in evaluation and faithfulness (e.g., benchmarks, LLM-as-judge, hallucination and groundedness detection, workflow verification).
• Experience in explainability and reliability (e.g., attribution and interpretability, uncertainty and calibration, monitoring for drift and failure).

• Strong record of impact through shipped AI systems or publications at top venues (such as NeurIPS, ICML, ICLR, ACL, EMNLP).
• Experience with foundation models, including tabular foundation models.
• No prior familiarity with finance or financial use cases required.

ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.