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.
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