Applied AI ML Lead
About The Position
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 own work from problem framing and experimentation through productionization, ensuring solutions are robust, scalable, and measurable. You will partner with product, engineering, and data teams to move ideas into production and improve outcomes through model development, evaluation, and operational excellence. You will also help raise the technical bar through mentorship, strong engineering practices, and continuous learning.
Requirements
- MS and/or PhD in Computer Science, Machine Learning, or a related field.
- At least 5 years of applied machine learning experience.
- At least 5 years of experience with a programming language such as Python, Java, or C/C++; intermediate Python proficiency is required.
- At least 5 years of experience applying data science and machine learning 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.
- Experience in advanced applied ML areas such as GPU optimization, fine-tuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (similarity search).
- Ability to complete tasks and projects with limited supervision.
- Attention to detail, follow-through, excellent communication skills, and a collaborative approach.
- Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.
Nice To Haves
- Experience with Ray, MLFlow, and/or other distributed training frameworks.
- In-depth understanding of search/ranking, recommender systems, graph techniques, and other advanced methodologies.
- Advanced knowledge in reinforcement learning or meta learning.
- Deep understanding of LLM techniques, including agents, planning, reasoning, and related methods.
- Experience building and deploying ML models on cloud platforms such as AWS and AWS tools such as SageMaker and EKS.
Responsibilities
- Serve as a subject matter expert on a wide range of machine learning techniques and optimizations.
- Provide in-depth knowledge of machine learning algorithms, frameworks, and techniques.
- Enhance machine learning workflows through advanced proficiency in large language models (LLMs) and related techniques.
- Conduct experiments using the latest machine learning technologies, analyze results, and tune models.
- Develop code to bring experimental results into production solutions in collaboration with engineering teams; own end-to-end Python code development for proof-of-concept, experimentation, and production-ready solutions.
- Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks.
- Collaborate 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.
- Drive decisions that influence product design, application functionality, and technical operations and processes.
Benefits
- Competitive total rewards package, with base salary determined by role, experience, skill set, and location.
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
- Comprehensive health care coverage.
- On-site health and wellness centers.
- Retirement savings plan.
- Backup childcare.
- Tuition reimbursement.
- Mental health support.
- Financial coaching.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
