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 Tensor Flow, Py Torch, 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