ML Engineer- Sr Consultant

About the role

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.

Responsibilities

• Deploy and productionize machine learning models developed by data science teams.
• Build and maintain model deployment pipelines, including packaging, testing, versioning, release management, and rollback processes.
• Optimize models and inference services for latency, throughput, scalability, reliability, cost, and resource efficiency.
• Support batch, streaming, real-time, and API-based model serving environments.
• Partner with data scientists to understand model logic, features, dependencies, validation metrics, and expected production behavior.
• Translate model artifacts and technical specifications into production-ready code and services.
• Implement monitoring for model performance, data quality, feature drift, model drift, latency, availability, and prediction quality.
• Support model validation, A/B testing, champion/challenger testing, and controlled rollout strategies.
• Contribute to MLOps capabilities such as CI/CD, model registries, feature stores, orchestration, observability, and automated testing.
• Troubleshoot production issues related to model serving, data pipelines, infrastructure, and performance.
• Ensure production ML solutions meet requirements for security, compliance, explainability, auditability, and operational resilience.

Requirements

• Basic Qualifications: 8 or more years of relevant work experience with a Bachelor Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD.
• Preferred Qualifications: 9 or more years of relevant work experience with a Bachelor’s Degree, or 7 or more years of experience with an Advanced Degree, or 3 or more years of experience with a PhD.
• Bachelor’s Degree in Computer Science, Engineering, Machine Learning, Statistics, Operations Research, Mathematics, or a related quantitative field, or equivalent experience.
• Experience deploying, operationalizing, or supporting machine learning models in production environments.
• Strong programming experience in one or more languages such as Python, Java, Scala, C++, C#, Go, or Rust.
• Understanding of machine learning concepts, including model training, feature engineering, validation, evaluation, and performance metrics.
• Experience building production software, APIs, data pipelines, or distributed systems.
• Experience with cloud platforms, containerized applications, or scalable data/ML infrastructure.