ML Engineer- Sr Consultant at Visa in Austin, TX

Job description

About Us 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. Job Description As a Machine Learning Engineer at the Senior Consultant/Senior Manager level at VISA, you will be responsible for deploying, optimizing, and maintaining machine learning models in production environments. You will work closely with data scientists, engineers, product teams, and platform teams to take models from experimentation into scalable, reliable, and secure production systems. This role requires a strong understanding of how machine learning models are built, trained, validated, and evaluated; however, the primary focus is not model research or development. Instead, the role is centered on productionizing models, optimizing inference performance, building deployment pipelines, monitoring model behavior, and ensuring long-term operational reliability. You will translate model artifacts and technical requirements into production-grade software, services, and pipelines using modern programming languages, cloud platforms, and MLOps practices. You will help ensure models are performant, explainable where required, well-monitored, and aligned with enterprise standards for security, compliance, and reliability. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools — for example, ChatGPT, Microsoft Copilot, and similar tools — to support everyday work. Key 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. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. 
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications 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 quantit