Applied AI ML Director
About The Position
The Chief Analytics Office (CAO) drives firmwide adoption of artificial intelligence and advanced analytics at JP Morgan, leading AI/ML strategy, governance, and product delivery. It oversees the development, adoption, and maintenance of AI solutions, balancing innovation with responsibility, security, and ethical practices. As a Generative AI Executive Director in the CAO, you will build and optimize production-grade LLM systems in the LLM Suite, which serves hundreds of thousands of professionals. You will architect scalable, reusable APIs and agentic workflows that process millions of documents and automate complex financial tasks. Working with ML Engineering, Product Management, and Cloud Engineering, you will deliver solutions that are measured, budgeted, reliable, scalable, and performant, with measurable business impact. This role focuses on production infrastructure rather than a research sandbox, and its technical decisions will influence how JP Morgan uses AI across the enterprise.
Requirements
- PhD or equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative discipline.
- Extensive hands-on experience as an individual contributor in ML engineering, with a proven track record of shipping production AI systems.
- Deep expertise in NLP, Computer Vision, and/or Multimodal LLM algorithms, with a strong foundation in statistics, optimization, and ML theory.
- Practical experience implementing distributed, multi-threaded, and scalable applications using frameworks such as Ray, Horovod, or DeepSpeed.
- Exceptional communication skills, including the ability to convey 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 (LoRA, QLoRA, IA3), model quantization (INT8, FP16, GPTQ), and quantization-aware training for LLMs at scale.
- Deep knowledge of distributed training strategies (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 across text, image, speech, and video for mission-critical LLM Suite products.
- Own end-to-end delivery, performance, and continuous improvement of individual LLM Suite products.
- Bridge advanced AI research with 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 shaping enterprise-scale AI infrastructure.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Director
Education Level
Ph.D. or professional degree
