Applied ML and Generative AI Leader, Executive Director

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Jersey City, NJ
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $246k
$174k most similar roles pay here $313k

This listing doesn't post a salary. Most similar roles pay $208,650–$283,837.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

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At a glance

TL;DR · Applied ML and Generative AI Leader, Executive Director

As an Applied ML and Generative AI Leader - Executive Director within the Corporate Technology team, you will provide hands-on leadership to design, build, and run production-grade machine learning and generative AI services for corporate functions. You will be responsible for establishing engineering standards, mentoring junior engineers through code reviews, and building MLOps capabilities including automated pipelines for deployment and monitoring. Your daily work involves developing LLM solutions, fine-tuning models for NLP tasks like summarization, and implementing RAG, Chain-of-Thoughts, and Tree-of-Thoughts strategies. You will utilize Python, TensorFlow, PyTorch, Scikit-learn, Docker, Kubernetes, and various cloud platforms to manage model lifecycles. The role requires translating complex technical capabilities into clear outcomes for non-technical stakeholders while ensuring all systems meet enterprise requirements for security, stability, and operational rigor across the corporate network.

What you'll do

  • Design, develop, and deploy production-grade ML and Generative AI solutions from concept to deployment.
  • Establish technical direction, architecture decisions, and engineering standards across multiple workstreams.
  • Build and institutionalize MLOps capabilities including automated pipelines for deployment, monitoring, and lifecycle management.
  • Fine-tune generative models and implement optimization strategies for specific NLP use cases like summarization.
  • Conduct thorough evaluations of generative models to iterate on architectures and improve performance.
  • Implement real-time monitoring mechanisms to ensure model reliability and operational stability.
  • Communicate AI capabilities and technical results to both technical and non-technical stakeholders.
  • Mentor junior engineers through design reviews, code reviews, and coaching to improve team quality.

What we're looking for

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 10+ years of engineering experience.
  • 3+ years building, deploying, and operating applied AI/ML systems in production including MLOps and governance.
  • Proficiency in Python for model development and integration with the OpenAI API.
  • Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and microservices.
  • Solid understanding of statistics, machine learning fundamentals, and generative model architectures like GANs and VAEs.
  • Expertise in RAG pipelines and advanced prompting strategies (preferred); familiarity with financial services (preferred).

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