The Microsoft CoreAI Post-Training team is dedicated to advancing post-training methods for both OpenAI and open-source models. Their work encompasses continual pre-training, large-scale deep reinforcement learning running on extensive GPU resources, and significant efforts to curate and synthesize training data. In addition, the team employs various fine-tuning approaches to support both research and product development. The team also develops advanced AI technologies that integrate language and multi-modality for a range of Microsoft products. The team is particularly active in developing code-specific models, including those used in Github Copilot and Visual Studio Code, such as code completion model and the software engineering (SWE) agent models. The team has also produced publications as by-products, including work such as LoRA, DeBerTa, Oscar, Rho-1, Florence, and the open-source Phi models.
We are looking for a Software Engineer 2 - Machine Learning with significant experience in large-scale model training, data curation, and hands-on coding. You will help in developing LLMs, SLMs, multimodal, and coding models using both proprietary and open-source frameworks. Key responsibilities include improving model quality and training efficiency through advanced techniques and data strategies, and managing the full pipeline from data ingestion, evaluation, to inference. Our team values startup-style efficiency and practical problem-solving. We are seeking a curious, adaptable problem-solver who thrives on continuous learning, embraces changing priorities, and is motivated by creating meaningful impact. Candidates must be self-driven, able to write high-quality code and debug complex systems, document their work clearly, and demonstrate solid experience in shipping ML systems.