Health Futures at Microsoft is seeking to advance next-generation AI tools and methods for health and life sciences by accelerating the training of generative models in collaboration with ML researchers, software engineers, and domain experts.
Requirements
- 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-Sharp, 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.
Responsibilities
- 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.
- Work across the stack from curriculum design, to debugging training runs, through developing new evaluation methods and high-performance inferencing.
- Train and optimize models on the latest hardware, devise new ways to assess their capabilities, and evolve data and training workflows to maximize model utility.
Other
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience 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.
- Demonstrated ability to communicate effectively and solve problems in collaborative, research-driven environment.
- Ensure regulatory compliance across ML workflows and data handling.
- Mentor engineers and researchers, promoting best practices in ML development, experimentation, and responsible AI principles.
