Applied AI ML Associate Sr

As an Artificial Intelligence Machine Learning Senior Associate within the Corporate Oversight and Governance Technology team, you will serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm s business objectives.

Job responsibilities

• Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
• Develop state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives.
• Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
• Implement optimization strategies to fine-tune generative models for specific NLP use cases, ensuring high-quality outputs in summarization and text generation.
• Conduct through evaluations of generative models (e.g., GPT-4), iterate on model architectures, and implement improvements to enhance overall performance in NLP applications.
• Developing monitoring model exploitability mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
• Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

Required qualifications, capabilities, and skills

• Bachelors or Masters degree in Computer Science, Engineering, or a related field
• Minimum 6 years of demonstrated experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes) and microservices design, implementation, and performance optimization.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs.
• Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.

Preferred qualifications, capabilities, and skills

• Familiarity with the financial services industries.
• Hand on experience in traditional AIML model building (XG Boost, Tree based algorithms)