Applied AI ML Director

Testing Site - JPMC; Jersey City (NJ); On-site; USD 190,000 - 230,000; Full time

Job summary

JPMorgan Chase is seeking an Applied AI / ML Director to lead a team of senior AI engineers in delivering production-grade agentic AI systems within Corporate Sector Team.

You will shape the technical direction for Corporate Technology AI, drive innovation, and foster responsible AI practices across multiple use cases with measurable business impact.

Qualifications

• 10 years of experience building and deploying applied AI/ML systems.
• Hands-on work and ability to explain technical problems with data-driven feedback.
• Foundational understanding of GPU infrastructure, Kubernetes and cloud.
• Proficiency with TF, PyTorch or Scikit-learn for production ML.
• Experience with ML Ops tools like MLflow and HPC frameworks like Ray.io/Slurm.

Responsibilities

• Lead hands-on development and set technical direction for GenAI and ML infra.
• Mentor senior AI engineers and drive production-grade AI systems.
• Collaborate with cross-functional teams to deliver enterprise AI initiatives.
• Define feature roadmaps, collect requirements, and ensure scalability.
• Address performance and technical debt through hands-on coding.

Skills

Leadership & mentorship

Stakeholder communication

Data-driven problem solving

Experimentation culture

Responsible AI

Architectural leadership

Technical roadmap planning

Education

MS/PhD in CS/ML/Statistics

Tools

NVIDIA DCGM

Kubernetes

Cloud platforms

TensorFlow

PyTorch

Scikit-learn

MLflow

vLLM

Ray.io

Slurm

Job description

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