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# Lead Machine Learning Engineer

- **Company:** JPMorgan Chase & Co.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Big Data, Cloud Computing, Nvidia CUDA, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Data Storage Technologies, Apache Spark, Kubernetes, Information Technology, Machine Learning Operations, Docker
- **Published:** August 22, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210771693

## About the Role

* BS in Computer Science or related Engineering field with 6+ years of experience Or MS degree in Computer Science or related Engineering field with 4+ years experience.
 * Solid knowledge and extensive experience in Python and in cloud computing, along with ML frameworks (i.e. pytorch, tensorflow)
 * Deep knowledge and passion for data science fundamentals, training and deploying models
 * Experience in monitoring and observability tools to monitor model input/output and features stats
 * Operational experience in big data/ML tools such as Ray, Spark and in training/inference systems such as Ray, vllm/SGLang
 * Solid grounding in engineering fundamentals and enterprise system design

Preferred qualifications, capabilities, and skills

 * Experience with recommendation and personalization systems is a plus.
 * CUDA experience is a big plus
 * Solid fundamentals and experience in containers (docker ecosystem), container orchestration systems [Kubernetes, ECS], DAG orchestration [Airflow, Kubeflow etc]
 * Good knowledge of data storage solutions and strategies (online and offline)

## Description

* Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters to support scalable machine learning workflows.
 * Develop and manage pipelines for model promotion and other capabilities related to MDLC.
 * Optimize training throughput for large data sources
 * Establish and maintain integrations to platforms and tools related to model monitoring and observability
 * Collaborate with cross-functional teams to integrate new technologies and improve the capabilities of our ML Platform.
 * Partner with product, architecture, modeling, and engineering to design robust solutions that power our Digital channels


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