<p>JobID: 210726857</p> <p>Category: Predictive Science</p> <p>JobSchedule: Full time</p> <p>Posted Date: 2026-03-31T14:36:57+00:00</p> <p>JobShift:</p> <p>Base Pay/Salary: Jersey City,NJ $128,250.00-$195,000.00</p> <p>Join a world-class data science team at JPMorgan Chase and help shape the future of our Chief Administrative Office. As a leader in applied AI and machine learning, you'll have the opportunity to work on high-impact projects that influence the way we do business across multiple domains. Collaborate with talented colleagues, leverage cutting-edge technologies, and see your work make a tangible difference. We value curiosity, technical excellence, and a passion for solving complex problems. If you're ready to accelerate your career and drive meaningful change, we want to hear from you.</p> <p>As an Applied AI ML, Sr. Associate in the Chief Data & Analytics Office, you will lead the development and deployment of innovative AI and machine learning solutions. You will collaborate with cross-functional teams to address complex business challenges, drive adoption of modern ML practices, and ensure responsible AI governance. You will have the opportunity to work with state-of-the-art technologies and contribute to a culture of technical excellence and continuous learning.</p> <p>Job Responsibilities:</p> <ul> <li>Lead the hands-on design, development, and deployment of advanced AI, GenAI, and large language model solutions. </li><li>Serve as a subject matter expert on a wide range of machine learning techniques and optimizations. </li><li>Collaborate with product, engineering, and business teams to deliver scalable, production-ready AI systems. </li><li>Conduct experiments using the latest ML technologies, analyze results, and tune models for optimal performance. </li><li>Own end-to-end code development in Python for both proof-of-concept and production-ready solutions. </li><li>Integrate generative AI within the ML platform using state-of-the-art techniques. </li><li>Drive adoption of modern ML infrastructure, tools, and best practices. </li><li>Optimize system accuracy and performance by identifying and resolving inefficiencies. </li><li>Communicate technical concepts and results to both technical and business stakeholders. </li><li>Ensure responsible AI practices, model governance, and compliance with regulatory standards. </li></ul> <p>Required Qualifications, Capabilities, and Skills:</p> <ul> <li>Master's or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field. </li><li>Minimum 3 years of hands-on experience in applied machine learning, including generative AI, large language models, or foundation models. </li><li>Experience programming in Python; experience with ML frameworks such as PyTorch or TensorFlow. </li><li>Proven experience designing, training, and deploying large-scale ML/AI models in production environments. </li><li>Understanding of prompt engineering, agentic workflows, and orchestration frameworks. </li><li>Experience with cloud platforms (AWS, Azure, GCP) and distributed systems (Kubernetes, Ray, Slurm). </li><li>Grasp of MLOps tools and practices (MLflow, model monitoring, CI/CD for ML). </li><li>Strong communication skills with the ability to explain complex technical concepts to diverse audiences. </li><li>Experience applying data science and ML techniques to solve business problems. </li><li>Passion for detail, follow-through, and technical excellence. </li></ul> <p>Preferred Qualifications, Capabilities, and Skills:</p> <ul> <li>Experience with high-performance computing and GPU infrastructure (e.g., NVIDIA DCGM, Triton Inference). </li><li>Familiarity with big data processing tools and cloud data services. </li><li>Experience with building and deploying ML models on cloud platforms such as AWS Sagemaker, EKS, etc. </li></ul>