The Corporate Technology team develops applications and provide technology support for all corporate functions across network. The application will cover the complete financial spectrum and across all divisions Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You will be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.

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

Bachelor's or Master's 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)