Staff ML Engineer (Bigdata, AI/ML)

As a Staff ML Engineer, you’ll have the opportunity to directly influence the development of AI-powered solutions that will drive business success and operational excellence at Visa. You’ll work on exciting AI and machine learning projects, collaborating with top-tier talent in a forward-thinking environment.

Key Responsibilities

1. Develop AI/ML-Powered Platforms. Create scalable, robust, and efficient machine learning platforms and applications to address complex business challenges.
2. Code Development. Write high-quality, maintainable, and efficient code in languages such as Java, Python, Rust, JavaScript, or Scala.
3. Machine Learning Pipelines. Build end-to-end machine learning pipelines for data preprocessing, feature engineering, model training, and evaluation.
4. End-to-End Development. Lead and manage the entire development cycle, from design and implementation to timely delivery of high-quality, business-aligned solutions.
5. Collaboration & Communication. Work closely with senior technical staff, project managers, and data scientists to deliver solutions that meet requirements and align with the architectural vision. Communicate complex technical concepts in an accessible and clear manner.
6. Risk and Issue Management. Track and manage risks and issues throughout the development process, ensuring they are resolved in a timely manner.

Basic Qualifications

1. Experience. 6+ years of professional experience with a Master’s degree in Computer Science, Computer Engineering, or a related field. Alternatively, 3+ years of relevant experience with a PhD.
2. Programming Expertise. Proficiency in one or more of the following programming languages, Java, Python, Scala, Go.
3. AI/ML System Development. Experience building and supporting scalable AI/ML systems using modern big data and machine learning technologies.
4. Database Knowledge. Familiarity with both MySQL and NoSQL databases like Cassandra, including data modeling, performance tuning, and cluster setup.
5. Machine Learning Lifecycle. Experience with the machine learning lifecycle, including data preprocessing, feature extraction, model training, deployment, and monitoring.
6. Interpersonal & Communication Skills. Strong leadership, facilitation, and communication skills, with the ability to present complex ideas in a simple and effective manner.

Preferred Qualifications

1. Open-Source Ecosystem. Experience with open-source machine learning tools such as MLflow, Cortex, Seldon, Kubeflow, or TFX.
2. Frontend Development. Experience with Single Page Applications (SPA) using frameworks like Angular is a plus.
3. Industry Experience. Background in the payment industry or working with AI-driven systems is advantageous.
4. Publications. Publications or presentations in recognized computing journals or conferences is a plus.

Visa's Commitment to Diversity

Visa is an Equal Employment Opportunity employer. We are committed to fostering an inclusive environment where everyone feels respected and valued. We encourage applicants of all backgrounds to apply. Visa also considers applicants with criminal histories in accordance with applicable laws and guidelines.

Why Visa?

At Visa, you’ll be joining a diverse and innovative team that is shaping the future of payments and technology. Whether you’re working on cutting-edge AI/ML projects, collaborating with brilliant minds, or contributing to the company’s strategic goals, you’ll have the opportunity to make a real-world impact.