Applied AI/ML Lead

Job Responsibilities Actively collaborate with Product, Technology, and other cross-functional teams to gain a deep understanding of complex business problems and formulate data-driven solutions to address these challenges in key areas of the payments domain. Design, develop, and deploy agentic systems using Large Language Models (LLM), machine learning and other AI solutions that meet success metrics aligned with business goals, while considering constraints such as model complexity, scalability, and latency. Partner with Risk and Compliance teams to ensure comprehensive model documentation, track performance metrics, and maintain adherence to regulatory compliance standards. Translate model outcomes into business impact metrics and communicate complex concepts to senior management and stakeholders. Required Qualifications Master’s degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research) with a minimum of 6 years of industry experience. Experience with Shell Scripting, Jupyter notebooks, SQL, PySpark, and AWS Cloud Services is required. Proficient in Python with hands‑on experience in Machine Learning and Deep Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit‑Learn, Pandas). Experience with Jupyter Notebook is essential. Extensive knowledge in the design and development of agentic systems and the tooling ecosystem such as LangChain, LangGraph, Model Context Protocol (MCP), DSPy, etc. Solid understanding of algorithms in machine learning, AI, and neural networks, including Large Language Models (LLM) and generative AI, as well as familiarity with state‑of‑the‑art practices and advancements in these domains. Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans. Strong cognitive and communication skills with clear and articulate expression. Excellent at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes. Extensive experience in Natural Language Processing (NLP) or Large Language Models (LLM), or Computer Vision and other machine learning techniques, including classification and regression algorithms. Preferred Qualifications Experience in the financial services industry, particularly within investment banking operations. Cloud computing experience with Amazon Web Services, Azure, Docker, Kubernetes, Databricks, and Snowflake. Familiarity with inference‑time algorithms such as Chain of Thought and sampling, etc. Benefits We offer a competitive total rewards package including base salary, commission‑based pay and/or discretionary incentive compensation in cash and/or forfeitable equity, along with comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching. Equal Opportunity We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. #J-18808-Ljbffr Aumni