remote
Vice President, Applied ML and Generative AI Lead - JPMorganChase
AI Engineer
Senior engineering leader driving design, development, and production deployment of machine learning and generative AI services, setting technical strategy and scaling solutions across the firm using Python, deep‑learning frameworks, cloud, and container orchestration.
About the role
Key Responsibilities
- Architect, build, and operate production‑grade ML and generative AI platforms supporting high‑throughput financial workloads.
- Lead a multidisciplinary team of data scientists, ML engineers, and software developers, fostering best practices in model development, testing, and monitoring.
- Define technical roadmaps, standards, and governance for large language model integration, ensuring scalability, security, and compliance.
- Collaborate with business stakeholders to translate strategic objectives into AI‑driven solutions, delivering measurable value.
- Drive adoption of MLOps pipelines, leveraging cloud services (AWS) and container orchestration (Kubernetes) for continuous delivery and robust model lifecycle management.
Requirements
- 10+ years of hands‑on experience in machine learning engineering, with deep expertise in Python and frameworks such as TensorFlow or PyTorch.
- Proven track record designing, deploying, and maintaining large‑scale generative AI or LLM solutions in production.
- Strong background in cloud platforms (AWS) and container technologies (Kubernetes/Docker) for scalable AI services.
- Experience leading high‑performing technical teams and establishing MLOps best practices.
- Excellent communication skills to bridge technical and business domains and influence senior leadership.
Skills
pythontensorflowpytorchawskubernetesmlops