Applied AI ML Lead

Responsibilities

• Serve as a subject matter expert on ML algorithms, frameworks, optimization techniques, and applied machine learning.
• Conduct experiments, analyze results, tune models, and transition prototypes into production-ready solutions.
• Develop end-to-end Python code for experimentation, proof of concept, and production systems.
• Apply LLMs, generative AI, embeddings, inferencing, prompt engineering, evaluation, and RAG techniques.
• Optimize model accuracy and system performance by identifying and resolving inefficiencies and bottlenecks.
• Collaborate with product, engineering, data, and ML teams to deliver business-focused solutions.
• Influence product design, application functionality, technical operations, and engineering processes.
• Mentor practitioners and raise technical standards through strong engineering practices and continuous learning.

Requirements

• An MS and/or PhD in Computer Science, Machine Learning, or a related field is required.
• At least 5 years of applied machine learning experience is required.
• At least 5 years of experience with a programming language such as Python, Java, or C/C++ is required, with intermediate Python proficiency required.
• At least 5 years of experience applying data science and ML techniques to business problems is required.
• Strong knowledge of NLP, LLMs, machine learning, deep learning, and frameworks such as PyTorch or TensorFlow is required.
• Experience with GPU optimization, fine-tuning, embedding models, inferencing, prompt engineering, evaluation, and RAG is required.
• Preferred experience includes Ray, MLFlow, distributed training, search and ranking, recommender systems, graph techniques, reinforcement learning, and meta-learning.
• Preferred experience includes LLM agents, planning, reasoning, and deploying ML models on AWS using tools such as SageMaker and EKS.
• Demonstrated leadership, cross-functional collaboration, communication, ownership, and ability to work with limited supervision are required.

Benefits

• The role offers a competitive total rewards package with benefits based on eligibility, including health care coverage, on-site wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching.
• The posting describes the position as part of JPMorganChase's Corporate Sector AI and Machine Learning and Data Platform team.