Visa
Fintech · Card network
Currently tracking 85 active AI roles, up 684% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $88k–$452k (avg $208k).
Fintech · Card network
| Title | Stage | AI score |
|---|---|---|
| Sr Site Reliability Engineer - Middleware, DevOps & Cloud This role focuses on applying AI & ML techniques to enhance the reliability, availability, and performance of Visa's middleware infrastructure. The engineer will develop intelligent automation systems, integrate ML models, and improve monitoring/observability, working with AI/LLM frameworks. The role involves supporting middleware software, designing reliability solutions, and collaborating with data science teams. Experience with DevOps, cloud platforms, and programming languages like Python, Java, or Go is required, with AI/ML engineering experience being a plus. | ServeData | 7 |
| Staff ML Scientist - PFI Staff ML Scientist at Visa focused on building, training, testing, validating, and productizing machine learning models. The role involves implementing MLOps best practices, utilizing AWS SageMaker, and understanding model explainability. Experience with deep learning frameworks and model serving is required, with a focus on fintech applications. |
| ServePost-train |
| 7 |
| Senior ML Engineer Senior ML Engineer at Visa focused on designing, developing, and deploying scalable machine learning products for online prediction. The role involves building and maintaining ML infrastructure and tooling, collaborating with cross-functional teams, and ensuring the performance and reliability of ML models in production. Experience with cloud platforms (AWS/GCP), Kubernetes, Vertex AI, Triton inference server, and ML lifecycle fundamentals is required. | Serve | 7 |
| Data Scientist Data Scientist role at Visa focused on developing and implementing risk models, analyzing transaction data using big data technologies, and deploying/monitoring these models in production. The role involves statistical analysis, machine learning, and potentially deep learning and NLP for risk assessment and product insights within the fintech domain. | Serve | 7 |