Senior
Applied AI/ML Lead
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Data Scientist Lead at JPMorgan Chase within the Asset and Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
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Design, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain
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Conduct 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.
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Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization
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Communicate effectively with both technical and non-technical stakeholders
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Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
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Develop and maintain tools and framework for prompt-based model training, evaluation and optimization
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Analyze and interpret data to evaluate model performance to identify areas of improvement
Required qualifications, capabilities, and skills
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Formal training or certification on software engineering concepts and 5+ years applied experience
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Experience with prompt design and implementation or chatbot application
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Strong programming skills in Python with experience in PyTorch or TensorFlow
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Experience building data pipelines for both structured and unstructured data processing.
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Experience in developing APIs and integrating NLP or LLM models into software applications
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Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
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Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
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Basic knowledge of deployment processes, including experience with GIT and version control systems
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Familiarity with LLM orchestration and agentic AI libraries
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Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment
Preferred qualifications, capabilities, and skills
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Familiarity with model fine-tuning techniques such as DPO and RLHF.
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Knowledge of Java, Spark
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Knowledge of financial products and services including trading, investment and risk management
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