What are the responsibilities and job description for the Senior Machine Learning Engineer - Visa AI as a Service position at Visa?
Ready to make a global impact by industrializing AI?
About the Role:
Visa AI as a Service (VAIaS) 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, VAIaS automates the updates to data, models, and applications. Combined with strong AI governance, VAIaS 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!
We are looking for a talented and versatile entry-level Machine Learning Engineer to join our growing team. In this role, you will be a key contributor to the full lifecycle of our core machine learning infrastructure. You will be responsible for both building our high-performance, low-latency model inference engine and ensuring its rock-solid reliability through a best-in-class observability platform.
This is a role for a strong software and machine learning engineering generalist who is passionate about building robust, scalable systems. You will be empowered to solve complex problems, write production-grade code, and make a significant impact on the systems that power our intelligent products.
Key Responsibilities:
- Design, build, and maintain the full lifecycle of our machine learning systems, from our low-latency inference engine to the observability platform that supports it.
- Develop and optimize high-performance, mission-critical services using languages like Rust, Python, and Go.
- Enhance the reliability and visibility of our MLOps ecosystem by building and scaling solutions for monitoring, logging, and tracing.
- Collaborate closely with data scientists and ML engineers to deploy, scale, and troubleshoot machine learning models in production.
- Write clean, high-quality, and well-tested code, and participate in code reviews to raise the bar for the entire team.
- Diagnose and resolve performance bottlenecks and system failures in our production environment.
If you are passionate about machine learning, model inference technology, large scale low latency system and are excited about making a significant impact, we would love to hear from you.
This is a hybrid position based in Austin, TX, allowing alternating between remote and office work. Expectations are to be in-office at least three days a week, aiming for a 50% office presence based on business requirements.
