JOB DESCRIPTION
As a Applied AI ML Sr Associate at JPMorgan Chase within the Corporate Sector – AIML Data Platforms, 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 hiring, leading, and mentoring a team of Machine Learning and Software 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
- Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage.
- Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques.
- Implement, deliver, and support high-quality ML solutions in partnership with a team of ML Engineers.
- Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions.
- 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.
- Lead 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.
Required Qualifications, Capabilities, and Skills
- Bachelor's degree or equivalent practical experience in a related field.
- 6+ years of experience in engineering management with a strong technical background in machine learning.
- 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.
- Strategic thinker with the ability to craft and drive a technical vision for maximum business impact.
Preferred Qualifications, Capabilities, and Skills
- Strong 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.
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