Teradata Staff AI Data Scientist

Company OverviewAt Teradata, we believe that people thrive when empowered with better information. Thats 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 worlds top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise. What Youll DoWe are seeking a Staff AI Data Scientist to provide technical leadership and strategic direction for training and finetuning language models across Teradatas AI platform. This role goes beyond individual execution; you will define best practices, influence architecture decisions, and mentor senior engineers while remaining handson with critical model training efforts. Define and lead the LLM/SLM training strategy, including model selection, data strategy, and alignment approaches.Architect scalable and reusable training and evaluation pipelines for instruction tuning, preference optimization, and synthetic data workflows.Establish evaluation standards and benchmarks for model quality, hallucination reduction, safety, and reliability across teams.Drive adoption of efficient finetuning and inference optimization techniques (PEFT, quantization, distillation) at platform scale.Partner with platform and infrastructure teams to influence training and serving architecture, GPU utilization, and cost efficiency.Mentor senior and midlevel data scientists and engineers, raising the overall bar for model quality and engineering rigor.Act as a technical advisor to product and leadership on LLM capabilities, limitations, and tradeoffs.Track cuttingedge research and proactively translate it into practical, enterpriseready solutions.Who Youll Work WithJoin forces with the best. You'll collaborate with a worldclass team of AI architects, ML engineers, and domain experts to build the next generation of enterprise AI systems. Product managers and UX designers to craft agentic workflows that are intuitive and impactful.Domain specialists to ensure solutions align with realworld business problems in regulated industries.Infrastructure teams to scale AI workloads globally.A rare opportunity to shape cuttingedge AI capabilities within a dynamic, datadriven company.Qualifications and QualitiesRequired B.S./M.S./Ph.D. in Computer Science, Machine Learning, AI, or a related technical field.Deep expertise in PyTorch, Transformers, and LLM training workflows.Proven experience designing endtoend model training and evaluation systems.Strong ability to influence technical decisions across teams.Preferred 6+ years of experience in ML/NLP, including LLM/SLM training at scale.Deep handson experience with SFT, DPO/RL-based alignment, and PEFT methods.Handson experience with finetuning methods, including full parameter updates and PEFT (LoRA/QLoRA).Experience with distributed training and inference at scale.Track record of technical leadership, mentorship, or crossteam impact. Company OverviewAt Teradata, we believe that people thrive when empowered with better information. Thats 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 worlds top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise. What Youll DoWe are seeking a Staff AI Data Scientist to provide technical leadership and strategic direction for training and finetuning language models across Teradatas AI platform. This role goes beyond individual execution; you will define best practices, influence architecture decisions, and mentor senior engineers while remaining handson with critical model training efforts. Define and lead the LLM/SLM training strategy, including model selection, data strategy, and alignment approaches.Architect scalable and reusable training and evaluation pipelines for instruction tuning, preference optimization, and synthetic data workflows.Establish evaluation standards and benchmarks for model quality, hallucination reduction, safety, and reliability across teams.Drive adoption of efficient finetuning and inference optimization techniques (PEFT, quantization, distillation) at platform scale.Partner with platform and infrastructure teams to influence training and serving architecture, GPU utilization, and cost efficiency.Mentor senior and midlevel data scientists and engineers, raising the overall bar for model quality and engineering rigor.Act as a technical advisor to product and leadership on LLM capabilities, limitations, and tradeoffs.Track cuttingedge research and proactively trans