Applied AI ML Lead
Lead applied AI/ML role in JPMorganChase's AI & ML and Data Platform team: take ML/deep learning solutions from problem framing and experimentation through production, with hands-on Python coding, LLM/Generative AI integration, performance tuning, and mentoring. Core tech: Python, PyTorch/TensorFlow, NLP/LLMs, RAG, AWS.
- Compensation
- Not disclosed
- Location
- Jersey City, NJ, United States
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- MS and/or PhD in Computer Science, Machine Learning, or related field with at least 5 years applied ML experience
- At least 5 years experience in Python, Java, or C/C++; intermediate Python is a must
- At least 5 years experience applying data science and ML techniques to business problems
- Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
- Experience with machine learning and deep learning methods
- Deep expertise in deep learning frameworks such as PyTorch or TensorFlow
- Experience in advanced applied ML areas: GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (similarity search)
- Ability to complete tasks and projects with limited supervision
- Passion for detail, excellent communication skills, team player
- Demonstrated leadership working with engineers, product managers, and other ML practitioners
Nice to have
- Experience with Ray, MLFlow, and/or other distributed training frameworks
- In-depth understanding of Search/Ranking, Recommender systems, and Graph techniques
- Advanced knowledge in Reinforcement Learning or Meta Learning
- Deep understanding of LLM techniques including Agents, Planning, and Reasoning
- Experience building and deploying ML models on AWS (Sagemaker, EKS, etc.)
Full description
Join a team where your work directly shapes how machine learning is applied at scale across the firm. You’ll partner with product, engineering, and data teams to take ideas from experimentation through production, improving outcomes through thoughtful model development, evaluation, and operational excellence.
As an Applied AI and Machine Learning Lead at JPMorganChase within the AI and Machine Learning and Data Platform team in Corporate Sector, you will drive the design and delivery of machine learning and deep learning solutions that solve meaningful business problems. You will take ownership from problem framing and experimentation through productionization, ensuring solutions are robust, scalable, and measurable. You will also help raise the technical bar through mentorship, strong engineering practices, and a culture of continuous learning.
Job responsibilities
- Serve as a subject matter expert on a wide range of ML techniques and optimizations.
- Provide in-depth knowledge of ML algorithms, frameworks, and techniques.
- Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
- Conducting experiments using latest ML technologies, analyzing results, tuning models
- Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions.
- Optimizing system accuracy and performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions.
- Integrate Generative AI within the ML Platform using state-of-the-art techniques.
- Drives decisions that influence the product design, application functionality, and technical operations and processes.
Required qualifications, capabilities, and skills
- MS and/or PhD in Computer Science, Machine Learning, or a related field, with at least 5 years of applied machine learning experience.
- At least 5 year's experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must.
- At least 5 years’ experience in applying data science, ML techniques to solve business problems.
- Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
- Experience with machine learning and deep learning methods.
- Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow.