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
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