Our Company
At Teradata, we believe that people thrive when empowered with better information. That's why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers--and our customers' customers--to make better, more confident decisions. The world's top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.
What You'll Do
Design, develop, and deploy AI/ML models and Generative AI solutions to enhance enterprise applications (CRM, ERP, CX, Finance).
Build and integrate machine learning pipelines into existing business systems and workflows.
Collaborate with product and platform teams to identify opportunities for AI-driven automation, insights, and personalization.
Fine-tune and optimize LLMs (Large Language Models) and other ML models for enterprise use cases.
Develop APIs and microservices to expose AI capabilities to broader platforms.
Ensure models meet requirements for accuracy, performance, scalability, and compliance (e.g., FedRAMP, GDPR).
Monitor, retrain, and improve deployed models using feedback loops and data pipelines.
Stay current with emerging AI/ML tools, frameworks, and best practices.
Who You'll Work With
Product Owners & Business Stakeholders - Understanding use cases and defining AI feature requirements.
Engineering & QA Teams - Integrating AI solutions into enterprise platforms and ensuring quality delivery.
Data Engineers & Data Scientists - Collaborating on model training, feature engineering, and data pipelines.
Cloud & Security Teams - Ensuring AI deployments meet compliance, governance, and scalability standards.
Global AI/Automation Practices - Aligning with corporate AI strategy and innovation initiatives.
What Makes You a Qualified Candidate
3-6 years of experience in AI/ML development or applied data science.
Strong programming skills in Python, Java, or Scala with experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).
Hands-on experience with LLMs, NLP, or Generative AI solutions.
Familiarity with MLOps tools (MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML).
Experience with APIs, microservices, and integrating AI into enterprise SaaS platforms.
Knowledge of SQL/NoSQL databases and data pipelines (Spark, Kafka, Airflow).
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