Applied AI/ML Lead Vice President, Payments

JPMorgan Chase

Confirmed live 2 days ago High trust

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Work type: On-site
Location: New York, NY
Posted: 122 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $210k

$164k most similar roles pay here $255k

This listing doesn't post a salary. Most similar roles pay $173,200–$246,150.

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 · Applied AI/ML Lead Vice President, Payments

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As a Vice President, Applied AI/ML Lead - Vice President - Payments within the JPMorgan Chase Payments team, you will own and drive the end-to-end delivery of high-impact AI/ML capabilities across the payments ecosystem. You will build and deploy production-grade systems to improve fraud detection, risk outcomes, and operational automation while managing constraints like latency, scale, and explainability. Your daily work involves developing state-of-the-art neural networks, including Transformer architectures, through fine-tuning, distillation, and model compression techniques. You will utilize Python, PyTorch or TensorFlow, SQL, Spark/PySpark, and AWS to build robust pipelines. The role focuses on solving complex problems in the payments lifecycle, such as transaction risk, anomaly detection, and routing optimization. You must translate complex model behaviors into actionable insights for stakeholders while ensuring rigorous governance and performance monitoring across all production models.

Skills

Neural Networks Transformers Python PyTorch TensorFlow SQL Spark PySpark AWS MLOps CI/CD Docker Kubernetes Databricks Snowflake Model Compression Feature Stores

What you'll do

Own the end-to-end delivery of AI/ML capabilities for fraud detection, risk management, and payment automation.
Design and build production-grade ML systems that balance accuracy, latency, throughput, and cost at scale.
Develop state-of-the-art neural architectures including Transformers, fine-tuning, and model distillation techniques.
Define rigorous evaluation metrics to translate model performance into measurable business impacts like loss reduction.
Establish model lifecycle standards for reproducibility, monitoring, drift detection, and incident response.
Ensure all models meet risk, compliance, and governance requirements regarding explainability and audit-readiness.
Lead technical decision-making through design reviews, code reviews, and mentoring of applied scientists and engineers.
Communicate complex model behaviors and trade-offs clearly to senior stakeholders and non-technical audiences.

What we're looking for

Master’s or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field.
6+ years of industry experience delivering applied ML (or a PhD with equivalent experience).
Proven track record of shipping production-grade ML models that deliver measurable business impact and undergo post-launch iteration.
Hands-on expertise in neural networks and Transformers, including fine-tuning, distillation, and model compression techniques.
Proficiency in Python with deep experience in PyTorch or TensorFlow and standard ML/data libraries.
Experience building data-driven systems using SQL and distributed processing frameworks like Spark or PySpark.
Experience deploying services and pipelines on AWS or equivalent cloud platforms at scale.
Ability to translate ambiguous business problems into structured ML plans and communicate complex trade-offs to non-technical stakeholders.

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