Applied AI ML Director

Join JPMorgan Chase and help shape the future of AI-driven innovation in financial services.

As an Applied AI / ML Director in Data Science & AI within Corporate Sector Team, you'll actively contribute to the development of machine learning and GenAI-powered applications, shape the technical direction of Corporate Technology AI, and drive innovation and efficiency within a highly collaborative environment. You will lead, mentor, and inspire a team of senior AI engineers to deliver production-grade agentic AI systems. You will partner with us to define technical direction, set engineering standards, and ensure operational excellence across multiple use cases. Your leadership will drive innovation, foster a culture of experimentation and responsible AI, and help us deliver solutions that make a measurable business impact. Together, we will build the next generation of AI systems for the firm.

Job Responsibilities

• Lead hands-on development efforts to drive the development and technical direction, focusing on the adoption of bleeding edge technology.
• Actively participate in coding, system architecture, and the implementation of GenAI and Machine learning infrastructure and applications.
• Implement complex ML infrastructure deployments to optimize and accelerate machine learning workloads.
• Effectively communicate complex features and systems in detail to stakeholders at all levels.
• Understand industry and company-wide trends to assess and implement new technologies, including integration technologies relevant to AI applications.
• Collaborate closely with cross-functional teams to improve the performance of the team and organization through hands-on technical leadership.
• Lead the technical vision and roadmap for enterprise initiatives, ensuring practical execution.
• Collect and synthesize requirements to create an effective feature roadmap and actively contribute to the development of those features.
• Identify and resolve performance and scalability issues, driving efforts to reduce technical debt through direct involvement in coding and system improvements.

Required Qualifications, Capabilities, and Skills

• 10 years of experience building and deploying applied AI/ML systems, with significant recent hands-on work
• Proficient in utilizing data and analysis to explain technical problems and provide detailed feedback and solutions.
• Foundational understanding of NVIDIA GPU Infrastructure software (e.g., NVIDIA DCGM, BCM, Triton Inference), Kubernetes and Cloud.
• Hands-on experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Experience in ML Ops and associated tooling like MLflow.
• Experience with High Performance Computing and Machine Learning frameworks such as vLLM, Ray.io, Slurm.
• Familiarity with cloud data services and big data processing tools.
• Familiarity with integration technologies relevant to AI applications.
• Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis.
• Understanding of information retrieval concepts, such as indexing, querying, and ranking.
• Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques.

Preferred Qualifications, Capabilities, and Skills

• Ability to communicate complex technical trade-offs to both technical and non-technical stakeholders
• Experience collaborating with cross-functional teams in a regulated environment
• Commitment to responsible AI practices and continuous improvement
• Ability to mentor and develop engineering talent
• Experience collaborating with cross-functional teams in a regulated environment