JPMorgan Chase is looking to solve complex machine learning problems and drive innovation in AI and ML solutions across teams, technologies, and projects.
Requirements
- Extensive hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
- Deep expertise in Cloud Engineering (AWS, Azure, GCP) and Distributed Micro-service architecture.
- Experienced with Kubernetes ecosystem, including EKS, Helm, and custom operators.
- Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems.
- Strong Python coding skills and experience in developing large-scale AI/ML systems.
- Proven track record in contributing to and optimizing open-source ML frameworks.
- Understanding & experience of AI/ML Platforms, LLMs, GenAI, and AI Agents.
Responsibilities
- Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions.
- Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage.
- Develop advanced monitoring and management tools for high reliability and scalability in AI/ML systems.
- Optimize AI/ML system performance by identifying and resolving inefficiencies and bottlenecks.
- Drive the adoption and execution of AI/ML Platform tools across various teams.
- Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques.
- Contribute to the entire AI/ML product life cycle through planning, execution, and future development by continuously adapting, developing new AI/ML products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth.
Other
- Bachelor's degree or equivalent practical experience in a related field.
- 5+ years of experience in engineering with a strong technical background in machine learning.
- Strategic thinker with the ability to craft and drive a technical vision for maximum business impact.
- Demonstrated ability to work effectively with engineers, data scientists, and ML practitioners.
- We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success.
