Executive Director, Applied AIML

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: New York, NY
Posted: 136 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $251k

$172k most similar roles pay here $314k

This listing doesn't post a salary. Most similar roles pay $215,900–$285,250.

Based on 239 similar postings.

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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 · Executive Director, Applied AIML

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As an Applied AIML -Executive Director within the Consumer & Community Banking Recommendations & Personalization team, you will lead the design and delivery of large-scale recommendation, ranking, and personalization systems. You will oversee end-to-end machine learning delivery, including candidate generation, retrieval, and real-time decisioning to improve customer engagement across digital channels. Your daily work involves developing evaluation frameworks for ranking, applying NLP and search/retrieval techniques like semantic retrieval and embeddings, and pragmatically integrating LLM-based methods for content understanding and synthetic labeling. You will manage a team of applied scientists and engineers while ensuring systems are reliable, secure, and scalable. Required skills include expertise in Python, Scala or Java, Spark, and distributed data processing. You will solve complex problems involving information retrieval, sequence models, and real-time personalization to enhance customer relevance and operational efficiency.

Skills

Machine Learning Recommender Systems NLP LLM GenAI Python Scala Java Spark Distributed Systems Information Retrieval A/B Testing Feature Stores Vector Search

What you'll do

Own and evolve large-scale recommendation, ranking, and personalization platforms across digital channels.
Lead end-to-end ML delivery including problem framing, feature strategy, model development, and A/B testing.
Develop and operationalize evaluation frameworks for ranking metrics, diversity, fairness, and long-term value.
Apply NLP and search retrieval techniques to enhance query understanding and recommendation quality.
Integrate GenAI tools into the recommendation stack for content understanding and synthetic labeling.
Build and lead a high-performing team of applied scientists and ML engineers.
Act as a hands-on technical leader by contributing to architecture, code paths, and system design.
Partner with cross-functional teams to align product roadmaps with measurable business impacts.

What we're looking for

PhD in Computer Science or equivalent experience in machine learning, recommender systems, ranking, personalization, or information retrieval.
Proven ability to lead and deliver large-scale production ML systems using big data and experimental methods.
Strong track record of people leadership including team building, technical direction, and mentorship.
10+ years of hands-on programming and system-building experience (PhD + industry).
Proficiency in Python and at least one other language such as Scala or Java.
Experience with Spark and distributed data processing systems.
Solid fundamentals in data structures, algorithms, distributed systems, and databases to build scalable ML services.
Excellent communication skills to influence senior stakeholders and translate business goals into technical outcomes.

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