Senior Research Engineering Scientist

The Core AI Model Training team leads research and engineering across the full lifecycle of large language model development for enterprise use cases including data curation pretraining fine tuning and evaluation. Our goal is to continuously improve our custom enterprise models by incorporating novel techniques and optimizing training and inference efficiency establishing a differentiated advantage for AI applications across the platform. These models are consumed across multiple business units to power a wide range of use cases enabling teams to solve complex problems and deliver tailored solutions. You'll help build the next generation of enterprise language models that bring AI experiences into our customers' day to day work serving more than 9000 enterprise customers worldwide. We're just getting started with our early adopter customers and we need your help building an amazing range of solutions. What you get to do in this role: • Confronted with real world challenges and datasets you will use your AI and ML expertise and creativity to apply existing methods and develop new ones to solve problems in a practical and scalable way. • Research propose implement train and evaluate models and techniques end to end. • Build and maintain training pipelines and evaluation harnesses that make results reproducible and progress measurable. • Collaborate daily with research scientists engineers and product managers to ship high quality high impact work. • Own your work from design through implementation testing and delivery partnering with product owners to translate requirements into results.   • Expertise in LLM post training including supervised fine tuning and distillation. • Expertise in reinforcement learning for LLMs including PPO GRPO DPO and reward modeling. • Hands on experience with training frameworks and distributed and large scale training including FSDP DeepSpeed and Megatron as well as parallelism strategies such as tensor pipeline expert and data parallelism. • Experience with synthetic data generation for training and evaluation. • Experience with data curation at scale including deduplication filtering and data mixture design. • Familiarity with a range of transformer architectures including decoder only or autoregressive encoder decoder and mixture of experts. • Expert level Python with strong OOP and design pattern fundamentals. • Ability to read current research and rapidly prototype and experiment with new ideas. • 3 or more years of relevant experience with a Bachelor's degree 3 or more years with a Master's degree a PhD or equivalent experience. Preferred Qualifications • Grounding in evaluation and benchmarking including building evaluation harnesses contamination checks and custom enterprise benchmarks. • Pretraining experience or an end to end perspective across pretraining and post training with an understanding of how choices in one stage propagate to the other. • Familiarity with inference and serving technologies such as vLLM or SGLang quantization and KV cache tradeoffs. • Publications at top tier venues such as ICLR NeurIPS ICML ACL EMNLP or AAAI. • Fluency with AI productivity tools such as Claude Code and Codex with a track record of thoughtfully integrating AI into engineering and research workflows.   For positions in this location, we offer a base pay of $185,500 - $315,400 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexibl