Applied ML and Generative AI Lead - Vice President
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 1mo ago
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Job Location
Jersey City, NJ, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
As the Applied ML and Generative Lead within J.P. Morgan, you will operate as a hands-on engineering leader responsible for designing, building, and running production-grade ML and Generative AI services, while setting technical direction that scales across multiple workstreams. You will remain close to the code and architecture decisions, establish delivery and engineering standards, and ensure solutions meet enterprise expectations for security, stability, and operational rigor. A core requirement is stakeholder partnership: you will routinely explain what is being built, why it matters, and how it will perform in production to both technical and non-technical audiences, enabling informed decisions and clear delivery alignment.
Responsibilities
- Provide hands-on technical leadership for designing, developing, and deploying ML/LLM/GenAI solutions from concept to production, ensuring reliability and operability.
- Collaborate with product managers, data scientists, ML engineers, and stakeholders to define requirements and prioritize use cases.
- Mentor junior engineers through design and code reviews, pairing, and coaching to improve engineering quality and delivery discipline.
- Build and institutionalize MLOps capabilities, including automated pipelines for deployment, monitoring, and model lifecycle management.
- Implement optimization strategies to fine-tune generative models for specific NLP use cases, focusing on summarization and text generation.
- Evaluate generative models, iterate on architectures, and implement improvements for enhanced NLP application performance.
- Implement real-time monitoring mechanisms to track model performance and ensure reliability.
- Communicate AI/ML/LLM/GenAI capabilities and results to diverse audiences.
- Stay updated on AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 7+ years of demonstrated experience in applied AI/ML engineering, with a track record of deploying business-critical ML models in production.
- Hands-on engineering leadership experience, including setting technical direction, making architecture decisions, conducting reviews, and mentoring junior engineers.
- Proficiency in Python for model development, experimentation, and integration with APIs like OpenAI.
- Experience with ML frameworks and libraries such as TensorFlow, PyTorch, and Scikit-learn.
- Experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and microservices.
- Solid understanding of statistics, machine learning fundamentals (classification, regression, deep learning, reinforcement learning), and generative model architectures (GANs, VAEs).
- Ability to identify and address AI/ML/LLM/GenAI challenges, optimize models, and fine-tune them for NLP applications.
- A portfolio showcasing successful generative model applications in NLP projects, including prompt engineering with OpenAI APIs.