The role involves engineering the future of global finance by designing and deploying advanced AI and machine learning systems at Citi
Job Summary
The role involves engineering the future of global finance by designing and deploying advanced AI and machine learning systems at Citi.
Candidates will oversee the entire MLOps lifecycle from data sourcing and feature engineering to production implementation and monitoring.
Employees enjoy a hybrid working model with up to two days at home per week, along with 27 days of annual leave and private medical care.
Matching Summary
The role involves engineering the future of global finance by designing and deploying advanced AI and machine learning systems at Citi.
Salary
Base: Competitive (annually reviewed); Bonus/Equity: Discretionary annual performance related bonus; Benefits: 27 days annual leave plus bank holidays, Private Medical Care & Life Insurance, Pension Plan
Skills & Requirements
Must-have
Python programming skills
TensorFlow PyTorch Scikit-learn proficiency
MLOps tools MLflow Kubeflow Docker Kubernetes
Cloud platforms AWS Azure GCP experience
Production deployment of NLP computer vision models
Nice-to-have
Consulting and project management techniques
Subject Matter Expertise for mentoring analysts
Experience with ethical AI and bias detection
Key Requirements
Bachelor's degree or equivalent experience
Substantial relevant experience in AI or Machine Learning Engineering
Proven track record of deploying ML models into production