As an Applied AI ML Senior Associate, within the Consumer Bank Sales Science Team, you will develop deep learning solutions and experiment with state of the art models and contribute to innovative projects and drive the future of field AI Technologies, leveraging ML tools and algorithms to deliver the right solutions as we reinvent CRMs and client/employee interactions at the firm.

Job responsibilities:

• Serve as a subject matter expert on a wide range of ML techniques and optimizations.
• Build and enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
• Conducting experiments using latest ML technologies, analyzing results, tuning models
• Actively engage in hands-on coding to convert experimental results into robust production solutions
• Take full ownership of the entire code development lifecycle in Python, from proof of concept and experimentation to delivering production-ready solutions.
• Integrate Generative AI within the ML Platform using state-of-the-art techniques.

Required qualifications, capabilities, and skills:

• MS and/or PhD in Computer Science, Machine Learning, or a related field; 3+ years of applied machine learning experience.
• Hands on experience in one of the programming languages like Python, R, Java, etc.
• hand on experience in applying data science, ML techniques to solve business problems.
• Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
• Experience with machine learning and deep learning methods.
• Deep understanding and expertise in deep learning frameworks such as Py Torch or Tensor Flow.
• Ability to work on tasks and projects through to completion with limited supervision.

Preferred qualifications, capabilities, and skills:

• In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies and advanced knowledge in Reinforcement Learning or Meta Learning.
• Software development experience is a plus and experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc
• Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.