The Principal Machine Learning Engineer will work within the Health Futures team, which focuses on developing AI tools for health and life sciences. This hands-on technical role involves collaborating with researchers and engineers to advance generative models and improve training processes. The engineer will engage in model training, data evaluation, and the development of AI-augmented scientific systems. The position emphasizes innovation and responsible AI practices in a dynamic, interdisciplinary environment.

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• Masters in Computer Science or related technical field AND 6+ years technical engineering experience including significant work in machine learning or applied AI OR equivalent experience.
• Proven track record of designing and deploying large-scale ML or MLops systems in research or product settings.
• Hands-on experience with large-scale distributed training of ML models.
• Deep expertise in ML algorithms, model optimization, and frameworks (e.g., PyTorch, TensorFlow).
• Experience with one or more of: optimizing data mixes, mid-training, post-training, model merging, or model distillation.
• Familiarity with security and compliance standards for enterprise and health data.
• Demonstrated ability to communicate effectively and solve problems in a collaborative, research-driven environment.

• Lead the design and development of machine learning models and systems for health and life sciences applications, ensuring scalability and reliability.
• Define technical strategy and architecture for ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment.
• Collaborate with interdisciplinary teams (including scientists, researchers, and software engineers) to envision and develop AI-augmented scientific systems.
• Mentor engineers and researchers, promoting best practices in ML development, experimentation, and responsible AI principles.
• Ensure security, privacy, and regulatory compliance across ML workflows and data handling.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.