Applied AI ML Director
About The Position
The Generative AI Executive Director will lead engineering for production-grade large language model systems within JPMorganChase’s Chief Analytics Office (CAO). The role focuses on building and optimizing LLM Suite infrastructure and products used at enterprise scale, including reusable APIs and agentic workflows that process large volumes of documents and automate financial tasks. The position collaborates with ML Engineering, Product Management, and Cloud Engineering to deliver reliable, scalable, performant solutions with measurable business impact. This is a production-infrastructure role rather than a research sandbox. The role’s technical decisions will shape enterprise AI capabilities, enabling other teams to build on shared infrastructure. It combines leadership of engineering teams with hands-on machine-learning engineering and end-to-end ownership of individual LLM Suite products. Employment offers are contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries, as required by Section 19 of the Federal Deposit Insurance Act. Compensation is based on role, experience, skill set, and location; eligible roles may also receive commission-based pay or discretionary incentive compensation. Benefits depend on eligibility.
Requirements
- PhD or equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative discipline.
- Extensive hands-on individual-contributor experience in ML engineering, with a proven record of shipping production AI systems.
- Deep expertise in NLP, Computer Vision, and/or Multimodal LLM algorithms, and a strong foundation in statistics, optimization, and machine-learning theory.
- Practical experience implementing distributed, multithreaded, scalable applications using frameworks such as Ray, Horovod, or DeepSpeed.
- Exceptional communication skills, including the ability to explain complex technical concepts and build trust with stakeholders at all levels.
Nice To Haves
- Advanced proficiency designing and deploying production ML pipelines using DAG frameworks, including custom operator development and pipeline optimization.
- Expertise architecting and implementing high-throughput, low-latency microservices with gRPC, REST, and GraphQL, including protocol buffer schema design, streaming endpoints, and load balancing.
- Hands-on experience with parameter-efficient fine-tuning methods such as LoRA, QLoRA, and IA3; model quantization such as INT8, FP16, and GPTQ; and quantization-aware training for LLMs at scale.
- Deep knowledge of distributed training strategies, including data, model, and pipeline parallelism, memory optimization, and inference acceleration for large-scale multimodal models.
- Experience with advanced agentic workflow orchestration, including multi-agent coordination, stateful task management, and integration with enterprise event-driven architectures.
Responsibilities
- Architect and deliver production LLM-based systems spanning text, image, speech, and video for mission-critical LLM Suite products.
- Own the end-to-end delivery, performance, and continuous improvement of individual LLM Suite products.
- Bridge advanced AI research and robust engineering to build innovative, production-ready solutions.
- Drive results with an entrepreneurial mindset in a fast-paced, high-impact environment.
- Lead engineering teams and make technical decisions that support reliable, scalable, performant enterprise AI infrastructure.
Benefits
- Comprehensive health care coverage
- On-site health and wellness centers
- Retirement savings plan
- Backup childcare
- Tuition reimbursement
- Mental health support
- Financial coaching
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
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What This Job Offers
Job Type
Full-time
Career Level
Director
Education Level
Ph.D. or professional degree
