at J.P. Morgan
Bulge Bracket Investment BanksPosted 4 days ago
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**Role: Applied AI ML Director, Palo Alto, CA, USA** Build, optimize, and scale production-grade Large Language Model (LLM) systems serving hundreds of thousands of professionals daily. Lead a cross-functional team to deliver innovative, real business-impact AI solutions. Key responsibilities include architecting robust, reusable APIs, agentic workflows, and processing millions of documents while automating complex financial tasks. Requirements: - PhD (or equivalent experience) in Computer Science, Mathematics, Statistics, or related field - Extensive ML engineering experience, with a proven track record 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 like Ray, Horovod, DeepSpeed - Exceptional communication skills with the ability to build trust and influence stakeholders at all levels Preferred Qualifications: - Advanced proficiency in designing and deploying production ML pipelines using DAG frameworks - Expertise in architecting and implementing high-throughput, low-latency microservices with gRPC, REST, and GraphQL - Hands-on experience with parameter-efficient fine-tuning, model quantization, and quantization-aware training for LLMs at scale - Deep knowledge of distributed training strategies, memory optimization, and inference acceleration for large-scale multimodal models - Experience with advanced agentic workflow orchestration and integration with enterprise event-driven architectures
- Compensation
- Not specified USD
- City
- Palo Alto
- Country
- United States
Currency: $ (USD)
Full Job Description
Location: Palo Alto, CA, United States
Architect and deliver production LLM based systems (text, image, speech, video) powering 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.
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, DeepSpeed, etc.
Exceptional communication skills, able to convey complex technical concepts and build trust with stakeholders at all levels.
Advanced proficiency in designing and deploying production ML pipelines using DAG frameworks, including custom operator development and pipeline optimization.
Expertise in 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/pipe 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.
FEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChases review of criminal conviction history, including pretrial diversions or program entries.
#LI-RB3
Lead delivery of production generative AI products and APIs that scale firmwide and drive measurable business outcomes.SIMILAR OPPORTUNITIES
Applied AI ML Director
Compensation
Not specified USD
City: Palo Alto
Country: United States
**Role: Applied AI ML Director, Palo Alto, CA, USA** Build, optimize, and scale production-grade Large Language Model (LLM) systems serving hundreds of thousands of professionals daily. Lead a cross-functional team to deliver innovative, real business-impact AI solutions. Key responsibilities include architecting robust, reusable APIs, agentic workflows, and processing millions of documents while automating complex financial tasks. Requirements: - PhD (or equivalent experience) in Computer Science, Mathematics, Statistics, or related field - Extensive ML engineering experience, with a proven track record 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 like Ray, Horovod, DeepSpeed - Exceptional communication skills with the ability to build trust and influence stakeholders at all levels Preferred Qualifications: - Advanced proficiency in designing and deploying production ML pipelines using DAG frameworks - Expertise in architecting and implementing high-throughput, low-latency microservices with gRPC, REST, and GraphQL - Hands-on experience with parameter-efficient fine-tuning, model quantization, and quantization-aware training for LLMs at scale - Deep knowledge of distributed training strategies, memory optimization, and inference acceleration for large-scale multimodal models - Experience with advanced agentic workflow orchestration and integration with enterprise event-driven architectures
Full Job Description
Location: Palo Alto, CA, United States
Architect and deliver production LLM based systems (text, image, speech, video) powering 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.
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, DeepSpeed, etc.
Exceptional communication skills, able to convey complex technical concepts and build trust with stakeholders at all levels.
Advanced proficiency in designing and deploying production ML pipelines using DAG frameworks, including custom operator development and pipeline optimization.
Expertise in 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/pipe 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.
FEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChases review of criminal conviction history, including pretrial diversions or program entries.
#LI-RB3
Lead delivery of production generative AI products and APIs that scale firmwide and drive measurable business outcomes.SIMILAR OPPORTUNITIES
