Senior Machine Learning Engineer - Cloud AI Platform/Infrastructure

About the position

Ready to make a global impact by industrializing AI? Visa AI as a Service (AIaS) operationalizes the delivery of AI and decision intelligence to ensure their ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud native platforms, AIaS powers and automates industrialization of data, models, and applications for predictive and generative AI. Combined with strong governance, AIaS optimizes the performance, scalability, interpretability and reliability of AI models and services. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, Visa AI as a Service is an ideal place for you! This role is for a Sr. ML Engineer – Cloud AI Platform, with a strong development background, whose primary objective will be to extend our AI as a Service platform to the Public Cloud while enhancing, optimizing our existing codebase and development procedures, as well as developing new solutions. We are seeking for a talented professional with a solid background in public cloud and AI/ML production systems. This role offers ample opportunities for learning and growth, and the chance to be part of delivering the next big thing for our AI as Services team. If you are passionate about cloud technology, AI, and machine learning, and are excited about making a significant impact, we would love to hear from you. This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Requirements

• 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
• Strong development experience in one or more the following programming languages: Python, Rust, Go, or Java
• 2 years of related experience with AWS, GCP, or Azure, preferably in an AI/ML production environment
• Proficiency in managing Cloud Identity and Access Management (IAM) solutions to ensure secure access control
• Experience with infrastructure as code (IaC) tools such as Terraform, Ansible, or CloudFormation
• Extensive experience with containerization and orchestration tools like Kubernetes, Helm or Docker
• Hands-on experience with model inference engines such as TensorFlow Serving, Triton, or other AI accelerators
• Excellent understanding of CI/CD pipelines and automation (e.g., with Github actions, Jenkins, Code Pipeline/Deploy)

Benefits

• Medical
• Dental
• Vision
• 401 (k)
• FSA/HSA
• Life Insurance
• Paid Time Off
• Wellness Program