Applied AI ML Lead, Chief Data & Analytics Office

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Jersey City, NJPlano, TX
Employment: Full-time
Posted: 75 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $217k

$159k $290k

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This listing doesn't post a salary. Most similar roles pay $179,687–$254,750.

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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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Applied AI ML Lead, Chief Data & Analytics Office

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The Applied AI ML Lead, Chief Data & Analytics Office leads the development and deployment of innovative AI and machine learning solutions within the Chief Administrative Office. This role involves leading the hands-on design, development, and deployment of advanced AI, GenAI, and large language model solutions to address complex business challenges. Key responsibilities include owning end-to-end code development, conducting experiments, tuning models for optimal performance, and ensuring responsible AI governance. The candidate will utilize Python, PyTorch, and TensorFlow to build scalable production-ready systems. Required technical skills include experience with prompt engineering, agentic workflows, and orchestration frameworks, alongside cloud platforms like AWS, Azure, or GCP and distributed systems like Kubernetes, Ray, and Slurm. The role also requires proficiency in MLOps tools like MLflow and CI/CD for ML.

Skills

Python PyTorch TensorFlow Generative AI Large Language Models MLOps AWS Azure GCP Kubernetes Ray Slurm MLflow CI/CD Prompt Engineering Agentic Workflows NVIDIA DCGM Triton Inference Sagemaker EKS

What you'll do

Lead the hands-on design, development, and deployment of advanced AI, GenAI, and large language model solutions.
Own end-to-end code development in Python for both proof-of-concept and production-ready solutions.
Integrate generative AI within the ML platform using state-of-the-art techniques.
Conduct experiments using the latest ML technologies and tune models for optimal performance.
Drive adoption of modern ML infrastructure, tools, and best practices.
Ensure responsible AI practices, model governance, and compliance with regulatory standards.
Mentor and guide other AI engineers and scientists to foster a culture of continuous learning.
Communicate technical concepts and results to both technical and business stakeholders.

What we're looking for

Master’s or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field.
Minimum 8 years of hands-on experience in applied machine learning, including generative AI, large language models, or foundation models.
At least 5 years of experience programming in Python and experience with ML frameworks such as PyTorch or TensorFlow.
Proven experience designing, training, and deploying large-scale ML/AI models in production environments.
Deep understanding of prompt engineering, agentic workflows, and orchestration frameworks.
Experience with cloud platforms (AWS, Azure, GCP) and distributed systems (Kubernetes, Ray, Slurm).
Solid grasp of MLOps tools and practices (MLflow, model monitoring, CI/CD for ML).
Experience with high-performance computing, GPU infrastructure, big data tools, or financial services background (preferred).

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