Join the Microsoft AI Superintelligence Team to develop advanced foundation models that enhance human potential while ensuring safety and alignment with human values. This role focuses on tackling complex deep learning challenges and requires collaboration with various teams to innovate and improve AI systems. The team values a growth mindset and aims to create a culture of inclusion where everyone can thrive. You will be part of a mission to deliver breakthroughs that positively impact society.

• Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline with 4+ years of technical engineering experience in coding languages such as C, C++, C#, Java, JavaScript, or Python.
• Master's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline with 8+ years of technical engineering experience in coding languages including Python and common data libraries.
• Experience with large-scale AI systems, including design and deployment of distributed architectures and proficiency with ML frameworks like PyTorch or TensorFlow.
• Expertise in data engineering for foundation models, including multimodal dataset design and understanding of Responsible AI principles.
• Background in LLM interaction and deployment, including practical work in prompt engineering and safety-aligned evaluation.

• Develop algorithms and design model architectures while conducting experiments.
• Improve training and deployment efficiency with a focus on detail and learning from all attempts.
• Follow a data-driven approach grounded in scientific analysis and meticulous ablation studies.
• Innovate and iterate over ideas, prototypes, and products.
• Collaborate closely with teams on infrastructure, data engineering, and product feedback.

• 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.