The Vice President-level Machine Learning Systems Engineer at Citi will lead the development of intelligent financial systems by architecting and maintaining scalable backend systems. This role bridges data science and production-ready systems, requiring collaboration with data scientists, front-end engineers, and business leaders. The focus is on operationalizing complex models and creating reliable backend services. The ideal candidate will have a strong background in ML Ops and a passion for redefining global finance through technology.

• 6+ years of professional experience implementing data-intensive, large-scale ML solutions.
• Expert-level proficiency in Python and Jupyter Notebook scripting.
• Experience with machine learning frameworks such as Scikit-learn, Keras, TensorFlow, and PyTorch.
• Familiarity with MLOps platforms like MLFlow and Google Cloud Vertex AI.
• Bachelor’s or Master’s degree in a technology-related discipline or equivalent professional experience.

• Take ownership of the ML systems architecture and resolve complex challenges.
• Mentor and develop emerging talent in best practices for building scalable systems.
• Direct comprehensive analytics and ML initiatives to address critical business challenges.
• Engage effectively with cross-functional stakeholders to align objectives.
• Ensure adherence to laws, regulations, and corporate policies while assessing risks.

• Citi offers a comprehensive benefits package including competitive pay, stock programs, healthcare coverage, retirement plans, paid time off, parental leave, and programs supporting employee wellbeing and professional development.