Staff ML Engineer

About this Team:

The AI Experimentation Platform (AIEP) team, a key component of the Data and AI Platform (DAP) technology organization within Visa, is at the forefront of harnessing the power of Artificial Intelligence (AI) to drive strategic growth and operational efficiency. The team is dedicated to developing an advanced platform that fosters technological innovation and delivers impactful solutions. This dedicated team is an integral part of Visa's commitment to harnessing AI's power, reflecting the company's forward-thinking approach to technological innovation. By creating an environment that fosters AI experimentation, they are paving the way for Visa's future growth and continued success.

As a Staff ML Engineer, you will have the unique chance to make a direct and meaningful impact by delivering solutions that powers AI systems. You will design, enhance, and build solutions dealing with the next generation AI/ML and GenAI technology and be an agent of transformation. We deliver and support strategic goals and have a lasting impact on our enterprise. We aim to stay ahead of the curve adapting to the advancement of Generative AI and keep our business miles ahead of our competitors.

Essential Functions:

• Develop platforms, applications, and solutions powered by machine learning to tackle business challenges and enhance product performance.
• Write high-quality, efficient, testable code using one or more of the programming language Java, Python, Rust, JavaScript and/or scala.
• Implement machine learning pipelines and workflows for data preprocessing, feature engineering, model training, and evaluation.
• Drive the development effort end-to-end for timely delivery of high-quality solutions that conform to requirements, conform to the architectural vision, and align with all applicable standards.
• Collaborate with senior technical staff and Project Managers to identify, document, plan contingency, track and manage risks and issues until all are resolved.
• Present technical solutions, capabilities, considerations, and features in business terms.
• Effectively communicate status, issues, and risks in a detailed and timely manner.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Requirements

Basic Qualifications:

• 6 years of work experience with a master’s degree in computer science/computer engineering or related field (e.g. Masters, MBA) or up to 3 years of relevant experience with a PhD.
• Experience programming in at least one or more in Java, Python, Scala and Go
• Strong understanding of algorithms and data structures
• Experience and/or academic background in building and supporting scalable, reliable data solutions and AI/machine learning powered systems using modern big data and ML/AI technologies.
• Experience with MySQL and NoSQL databases such as Cassandra, including data model design, cluster setup, and performance tuning.
• Hands-on experience with web service standards and related patterns (REST, gRPC).
• Hands-on experience and/or academic background developing systems for the machine learning lifecycle: data preprocessing and feature extraction, model training and evaluation, and deployment and monitoring.
• Hands-on experience and/or academic background partnering with data scientists and can speak knowledgeably about the major machine learning paradigms, algorithms, software tools, infrastructure and workflow needs.
• Strong interpersonal, facilitation, and leadership skills along with effective communication (both written and verbal) skills and the ability to present complex ideas in a clear, concise way.

Preferred Qualifications:

• Familiarity with the associated open-source ecosystem (e.g., mlflow, cortex, seldon, Kubeflow, tfx) is a plus.
• Knowledge and experience working on Single Page Applications development using Angular or similar framework is a plus.
• Publications or presentations in recognized computing journals/conferences is a plus.
• Payment industry experience is a plus.