Our Company

At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.

What You’ll Do

• Transform advanced AI and analytics research prototypes into production-ready, scalable, and maintainable solutions that can be confidently deployed to customers.

• Strengthen the connection between research and real-world delivery by improving code quality, documentation, testability, and operational maturity across research outputs.

• Build automation frameworks, CI/CD pipelines, and tooling that enable the organization to scale through technology rather than headcount.

• Establish and uphold engineering quality standards that ensure successful and consistent transitions from prototype to production.

• Achieve success by enabling Teradata’s research innovations to reliably reach customers in the form of robust, high-performance systems.

Who You’ll Work With

• Operate within the Office of the Chief Technology Officer (OCTO), focusing on applied AI, advanced analytics, and emerging technology prototypes.

• Play a critical role in accelerating the translation of research concepts into customer-ready capabilities for Teradata’s product and service organizations.

• Collaborate closely with research engineers, product teams, and service delivery teams to align technical direction, architectural decisions, and deployment needs.

• This position reports directly to the VP of Advanced Research within OCTO.

What Makes You a Qualified Candidate

• Expertise in Python, Go, or C/C++.

• Strong understanding of CI/CD automation tools, GitHub workflows, and SQL/database design.

• Demonstrated ability to write clean, testable, well-documented code.

• Experience working with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.

• Practical experience using AI-assisted development tools (e.g., GitHub Copilot, Claude).

What You’ll Bring

• Experience transforming research or prototype code into production-quality software.

• Familiarity with distributed systems, scalability patterns, and performance optimization.

• Experience with containerization, cloud deployment, or infrastructure-as-code workflows.

• Background in research, innovation teams, or model-deployment pipelines.

• Understanding of AI governance, ML testing frameworks, and responsible-AI principles.

• Master’s degree in Computer Science or equivalent expertise is a plus.

• Contributions to open-source projects or a strong public portfolio.

• Knowledge of inference optimization or productionizing machine learning systems.

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