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JPMorgan Lead Site Reliability Engineer United States, New Jersey, Jersey City 596286045
Yesterday
Job Responsibilities:
- Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
- Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain.
- Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
- Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.
- Communicate effectively with both technical and non-technical stakeholders, including senior leadership.
- Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
- Develop and maintain tools and frameworks for prompt-based model training, evaluation, and optimization.
- Analyze and interpret data to evaluate model performance and identify areas of improvement.
Required qualifications, capabilities, and skills:
- Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.
- Hands-on experience in building Agentic AI solutions.
- Familiarity with LLM orchestration and agentic AI libraries.
- Strong programming skills in Python with experience in PyTorch or TensorFlow.
- Experience building data pipelines for both structured and unstructured data processing.
- Experience in developing APIs and integrating NLP or LLM models into software applications.
- Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
- Excellent problem-solving skills and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner.
- Basic knowledge of deployment processes, including experience with GIT and version control systems.
- Hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.
Preferred Qualifications, Capabilities, and Skills:
- Familiarity with model fine-tuning techniques.
- Knowledge of financial products and services, including trading, investment, and risk management.
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