Software Engineer 2 – Machine Learning

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.

Responsibilities

Responsibilities

• Collaborate with senior engineers and researchers to build and optimize training and inference pipelines for LLMs, SLMs, multimodal, and code-specific models.
• Contribute to the deployment and monitoring of models in production environments.
• Write clean, efficient, and maintainable code for ML systems.
• Help improve inference performance, reliability, and scalability.
• Participate in rapid experimentation cycles and support integration with Microsoft products.
  
  

Qualifications

Required Qualifications

• Bachelor’s or master’s degree in computer science, Engineering, or a related field, or equivalent practical experience.
• 3+ years of professional experience, including 2+ years with Python and ML frameworks such as PyTorch or TensorFlow.
• Hands-on experience with training or fine-tuning LLMs or multimodal models.
• Familiarity with production ML systems and concepts like model serving, caching, batching, and monitoring.
• Understanding of distributed systems and cloud-based infrastructure.
  
  

Preferred Qualifications

• Experience with containerization tools (e.g., Docker, Kubernetes).
• Exposure to MLOps or DevOps practices (CI/CD, automated testing, deployment).
• Interest in generative AI and open-source model ecosystems.
• Ability to work in a fast-paced, collaborative environment with a growth mindset.
• Strong communication and documentation skills.
  
  

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Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.