Drimva

JPMorgan Chase

Applied AI ML-Vice President

$138K–$260K

New York, NY +3 · Director · Full-time · Posted Apr 8, 2026

Location
New York, NY
Plano, TX
Palo Alto, CA
Jersey City, NJ
Experience
Undergraduate degree with 3+ years OR master’s degree with 2+ years; training and work experience in LLM/NLP and search.
Education
Undergraduate or master’s degree in Computer Science.

About the job

Designs, builds, and scales NLP solutions for customer and internal-agent operational workflows, from model development through production monitoring and iteration.

What you'll do

  • Develop production-grade language capabilities, including intelligent search, summarization, classification, and next-best-action recommendations.
  • Apply NLP and machine learning expertise to solve complex business problems and contribute across the product development lifecycle.
  • Evaluate model performance, improve data quality and feedback loops, and monitor and refine production solutions for reliability, security, and scale.

What they ask for

  • Undergraduate degree with 3+ years OR master’s degree with 2+ years in Computer Science, with training and work experience in LLM/NLP and search.
  • Strong written and oral communication skills to present analytical findings and influence project stakeholders.
  • Advanced programming skills in more than one language; examples include Spark, Python, Scala, and Java.
  • Hands-on understanding of data structures, algorithms, operating systems, compilers, databases, and systems.

Nice to have

  • Undergraduate and master’s degrees in computer science with concentration in NLP or search experience.
  • Experience developing large-scale machine learning solutions based on big data, such as classification, regression, or recommender systems.

Pay

$171,000.00-$260,000.00 USD base salary; $137,750.00-$235,000.00 USD base salary; $171,000.00-$260,000.00 USD base salary; $171,000.00-$260,000.00 USD base salary

Tools

LLM, NLP, Spark, Python, Scala, Java

AI focus

Applies NLP and machine learning, including LLM-based methods where appropriate, to build language capabilities for operational workflows; work includes search, summarization, classification, recommendations, model evaluation, monitoring, and iteration.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 6, 2026 (UTC)