Machine Learning Engineer

Visa’s Technology Organization 

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce through AI‑powered payment technologies. We operate one of the world’s most sophisticated processing networks, capable of handling tens of thousands of secure transactions per second across millions of merchants, financial institutions, and consumers worldwide. 

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. 

The Opportunity 

We are looking for talented, curious, and impact‑driven Machine Learning Engineers who enjoy solving complex problems using a combination of software engineering, data engineering, and applied machine learning. 

As part of a cross‑functional product team, you will design, build, deploy, and operate ML solutions that directly support Visa’s core payment platforms and value‑added services. Your work will move beyond experimentation into real‑world production systems that must meet strict requirements for reliability, performance, security, and compliance. 

The Work Itself:

• Design, build, and operate production‑grade machine learning systems that run at Visa’s global scale for NLP and related workloads with strict latency and throughput targets.
• Develop end‑to‑end ML pipelines covering data preparation, model training, validation, deployment, monitoring, and retraining. 
• Build and maintain high-availability, fault-tolerant ML services and APIs, including load balancing and robust autoscaling for GPU inference. 
• Design and implement advanced agentic AI systems: RAG pipelines, multi-step and branching agents, actor–critic control loops, validation/guardrail stages, and custom tools. 
• Work closely with product, data, and platform teams to turn requirements into concrete ML system designs and production deployments across multiple Visa technology offerings. 
• Continuously improve model quality, data quality, system reliability, and cost/performance of the ML stack. 

Essential Functions:

• Own ML model and service implementations end to end, from prototype to production. 
• Apply MLOps practices for safe, repeatable deployment, monitoring, and lifecycle management of models and agents. 
• Engineer scalable APIs and serving layers that integrate cleanly with existing systems and downstream applications. 
• Use solid data structures, algorithms, and time/memory complexity analysis to make sound, scale-aware design choices. 
• Participate in technical design reviews and architecture discussions, contributing an ML and systems perspective. 
• Debug and optimize CPU/GPU inference, data pipelines, and distributed workloads in collaboration with other engineers. 

This role is designed for engineers who want to build strong foundations in software engineering and applied machine learning while working on real‑world, production systems at Visa scale. The role focuses on contributing to ML pipelines, model deployment, and scalable services within a cross‑functional team, with strong mentorship and hands‑on learning. Prior professional experience is not required; success is driven by solid fundamentals, curiosity, and a willingness to grow into end‑to‑end ML system ownership.