AI / ML Director

evaluation.Build and integrate agent tools (MCP) and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing, error handling, and retries.Design and implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics.Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations.Deploy scalable AI services to cloud infrastructure, ensuring monitoring, and observability for agent performance.Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics, and feedback loops to continuously improve reliability and utility.Partner with stakeholders to define requirements, design intuitive human-AI interfaces (voice, chat), and deliver measurable business impact.Analyze data to inform agent

capabilities, optimize retrieval, and drive data-driven decision-making; and performance evaluations.Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices.Required qualificationsMSc/PhD in Computer Science, Data Science, Machine Learning, or related field.Significant proven experience building and deploying AI applications in large scale production environments.Experience managing data science teams and couching team membersProficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).Experience with generative models (transformers, GANs/VAEs; diffusion models a plus).Strong understanding of data preprocessing, feature engineering, and evaluation techniques.Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).Strong communication skills for both technical and non-technical audiences.Preferred

qualificationsExperience fine-tuning small language models (SLMs) with LoRA, QLoRA, DoRA; quantization and distillation a plus.Familiarity with prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites.Experience with distributed computing, data sharding, and performance optimization.Hands-on with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration.Demonstrated experience in financial services, particularly investment banking operations.J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are
directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and
extends liquidity in markets around the world. Full timePosting Date: 2026-02-03