Sr. AI/ML Engineer - Cybersecurity

Join us in shaping the future of Generative AI at Visa and making a significant impact on the enterprise.

You will have the opportunity to work across various roles from development to architecture and collaborate closely with a cross-functional team of architects, engineers, data scientists, and product managers to design, implement, and deliver solutions that are intuitive, user-centric, and accessible to everyone at Visa.

The Cyber Analytics and AI Innovation team is revolutionizing the field of machine learning and artificial intelligence by developing cutting-edge capabilities and tools that empower employees at Visa to develop secure applications with higher productivity. We are a dynamic and innovative team, driven by a passion for AI/ML technology and a commitment to delivering exceptional platforms and services to our business partners at Visa.

We are at the forefront of innovation, developing a suite of cutting-edge, Secure Enterprise AI Applications that are set to redefine the landscape of Gen AI. Our projects include:

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 three days a week, Tuesdays, Wednesdays, and Thursdays, with a general guidepost of being in the office 50% of the time based on business needs.

Basic Qualifications:
2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

Preferred Qualifications:
3 or more years of work experience with a Bachelor s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
Minimum of 3+ years of experience in developing highly available and scalable RESTful services using Python. Experience with Java, Go, Rust or any other object-oriented programming language is a plus.
Hands-on experience with design and development tools like IntelliJ, VSCode, Postman, and Jupyter.
Expertise in evaluating various large language models (LLMs), assessing their performance, and comparing their capabilities to identify suitable models based on business requirements.
Proven experience in machine learning model fine-tuning and optimization.
Strong knowledge of knowledge graph construction and management.
Proficiency in vector embedding techniques and their applications.
Hands-on experience with AI model APIs and AI agent frameworks.
Experience with deep learning frameworks such as TensorFlow, PyTorch, or similar.
Familiarity with the Nvidia ecosystem, including CUDA, and other relevant tools.
Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure).
Proficiency in working with both RDBMS (preferably MySQL) and NoSQL databases (preferably Cassandra).
Knowledge of Git for version control
Ability to multi-task in a dynamic and fast paced environment.
Solid understanding of software development best practices and principles.
Experience with Agile methodologies and practices.
Strong analytical and problem-solving skills with attention to detail.
Excellent communication skills, both written and verbal, to effectively collaborate with cross-functional teams.