Senior Associate-Applied Artificial Intelligence / Machine Learning

Join an Applied Artificial Intelligence and Machine Learning team that takes Generative AI and Machine Learning applications from prototype to production for a Global Banking business. You will work in a collaborative, inclusive environment with opportunities to build technical depth.
As a Senior Associate–Applied Artificial Intelligence / Machine Learning in the Applied Artificial Intelligence and Machine Learning team, you will help solve exciting business challenges for a Global Banking business within a leading global financial institution. You will work with product, business, and engineering partners to turn business problems into AI/ML solutions, balancing accuracy, latency, cost, and risk, and deliver them reliably in a regulated environment. You will apply sound technical judgment to balance business needs with technical constraints, contribute to experimentation and validation, and help productionize scalable and trustworthy solutions. You will also engage in knowledge sharing through enterprise machine learning communities.
Job responsibilities
Collaborate with an Artificial Intelligence and Machine Learning (AI/ML) team to contribute to projects within a global organization and support an inclusive culture with a growth mindset
Assist in setting the technical vision and executing strategic roadmaps to drive AI innovation
Design, build, and iterate on generative AI and machine learning applications
Evaluate large language model (LLM)-powered applications using curated test sets, metrics, automated and LLM-based scoring, human review, and regression testing, and use the results to drive improvements
Partner with engineering teams to productionize solutions, and monitor quality, latency, and cost once deployed
Work with product and business partners to translate requirements into AI/ML specifications, define milestones, and deliver using Agile methodology
Apply responsible AI practices, including explainability, and meet model risk and governance requirements in a regulated environment
Required qualifications, capabilities, and skills
Three years of experience developing AI/ML applications, with an advanced degree in Computer Science, Data Science, Statistics, or an equivalent field, or equivalent practical experience
Hands-on experience building applications with large language models (LLMs), including prompt engineering, context management, and output parsing
Experience evaluating AI/ML systems, including designing metrics, test sets, and experiments for non-deterministic outputs
Knowledge of data structures, algorithms, machine learning, data mining, and information retrieval
Hands-on experience applying classical machine learning (for example, linear models, tree-based ensembles, clustering) and deep learning (for example, neural networks, transformers), including feature engineering, model training, and validation
Proficiency in Python with hands-on experience in machine learning and deep learning frameworks (PyTorch, scikit-learn) and generative AI ecosystems (Hugging Face, large language model application programming interfaces, LangChain/Google ADK)
Experience using version control, code review, and testing practices
Collaboration skills and the ability to communicate effectively with both technical and non-technical audiences
Preferred qualifications, capabilities, and skills
Experience with agentic patterns, including tool calling, multi-step orchestration, and human-in-the-loop review
Familiarity with at least one of the following areas: Knowledge Graphs, Computer Vision, Reinforcement Learning, Recommender Systems, or Time Ser