Chase
Applied AI ML Lead
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As an Applied AI ML Lead at JPMorgan Chase within the CCB Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery. You will be responsible for leading, and mentoring a team of Machine Learning and Artificial Intelligence Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key. Job Responsibilities Lead a team of machine learning engineers, ensuring the delivery and support of high-quality ML solutions. Collaborate with product teams to deliver tailored AI/ML-driven technology solutions. Architect and implement robust, cloud-native MLOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production. Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products. Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems. Optimize system performance by identifying and resolving inefficiencies and bottlenecks. Drive the adoption and use of AI/ML platform tools across teams. Define and enforce robust AI governance and Responsible AI frameworks, ensuring all solutions are fair, transparent, and compliant with regulatory requirements. Oversee the full AI/ML product lifecycle, from planning and execution to future development, adapting and developing new products and methodologies to meet business goals. Mentor and develop a team of AI/ML professionals, promoting a culture of excellence, continuous learning, and professional growth. Required Qualifications, Capabilities, and Skills Bachelor's degree or PhD or Master's in Computer Science, Engineering, Data Science, or related field 5+ years of experience in Machine Learning and Artificial Intelligence engineering. Extensive hands-on technical experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn). Deep expertise in cloud engineering (AWS, Azure, GCP) and distributed microservice architecture. Experience with Kubernetes ecosystem, including EKS, Helm, and custom operators. Background in high performance computing and ML hardware acceleration (GPU, TPU, RDMA). Strategic thinker with the ability to drive technical vision for business impact. Demonstrated leadership working effectively with engineers, data scientists, and ML practitioners. Preferred Qualifications, Capabilities, and Skills Strong coding skills and experience developing large-scale AI/ML systems. Proven track record contributing to and optimizing open-source ML frameworks. Recognized thought leader in the field of machine learning. Hands-on experience with generative AI and LLMs in production settings. Cloud AWS Machine Learning Certification or any GenAI Certifications
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As an Applied AI ML Lead at JPMorgan Chase within the CCB Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery. You will be responsible for leading, and mentoring a team of Machine Learning and Artificial Intelligence Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key. Job Responsibilities Lead a team of machine learning engineers, ensuring the delivery and support of high-quality ML solutions. Collaborate with product teams to deliver tailored AI/ML-driven technology solutions. Architect and implement robust, cloud-native MLOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production. Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products. Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems. Optimize system performance by identifying and resolving inefficiencies and bottlenecks. Drive the adoption and use of AI/ML platform tools across teams. Define and enforce robust AI governance and Responsible AI frameworks, ensuring all solutions are fair, transparent, and compliant with regulatory requirements. Oversee the full AI/ML product lifecycle, from planning and execution to future development, adapting and developing new products and methodologies to meet business goals. Mentor and develop a team of AI/ML professionals, promoting a culture of excellence, continuous learning, and professional growth. Required Qualifications, Capabilities, and Skills Bachelor's degree or PhD or Master's in Computer Science, Engineering, Data Science, or related field 5+ years of experience in Machine Learning and Artificial Intelligence engineering. Extensive hands-on technical experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn). Deep expertise in cloud engineering (AWS, Azure, GCP) and distributed microservice architecture. Experience with Kubernetes ecosystem, including EKS, Helm, and custom operators. Background in high performance computing and ML hardware acceleration (GPU, TPU, RDMA). Strategic thinker with the ability to drive technical vision for business impact. Demonstrated leadership working effectively with engineers, data scientists, and ML practitioners. Preferred Qualifications, Capabilities, and Skills Strong coding skills and experience developing large-scale AI/ML systems. Proven track record contributing to and optimizing open-source ML frameworks. Recognized thought leader in the field of machine learning. Hands-on experience with generative AI and LLMs in production settings. Cloud AWS Machine Learning Certification or any GenAI Certifications