Description We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan Chase within the AI and Machine Learning Data Platform Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build solutions that automate quality workflows, accelerate debugging, and enable smarter decision-making across SDLC. Join us in shaping the future of intelligent testing through cutting-edge AI and model-driven engineering. Job responsibilities Serves as a subject matter expert on a wide range of ML techniques and optimizations. Provides in-depth knowledge of ML algorithms, frameworks, and techniques. Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has 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. Optimizes 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. Integrates Generative AI within the ML Platform using state-of-the-art techniques. Required qualifications, capabilities, and skills MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience. Experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must. Experience in applying data science, ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on 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, RAG (Similarity Search). Ability to work on tasks and projects through to completion with limited supervision. Passion for detail and follow through. Excellent communication skills and team player Preferred qualifications, capabilities, and skills Master’s degree in computer science, ML or related areas Experience with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. Experience working with large-scale MLOps pipelines, working with and deploying models to production services.