This role is part of Microsoft AI's Superintelligence Team, focusing on building infrastructure for training, evaluation, and deployment of advanced AI models. The team aims to create AI systems that enhance human potential while ensuring safety and control. You will work collaboratively with engineering and research teams to improve the efficiency and reliability of AI model deployment across Microsoft products. The position emphasizes a culture of inclusion and values individuals who are ambitious yet humble.

• Strong software engineering fundamentals in building large-scale, production systems.
• Hands-on ownership of production infrastructure.
• Proficiency in Python as a primary language in production systems.
• Experience with Kubernetes and containers for deploying and operating production workloads.
• Experience in building or operating platform services such as job orchestration and data/compute pipelines.
• Familiarity with production operations ownership, including monitoring, logging, alerting, and incident response.
• Experience on cloud platforms, preferably Azure, with acceptable knowledge of AWS or GCP.
• Comfort with distributed systems, networking, and storage.

• Design and build core platform services for scalable training and evaluation.
• Standardize containerized workflows by maintaining Docker images and CI/CD configurations.
• Implement end-to-end observability and operations through metrics, tracing, and logging.
• Architect and operate services on Azure cloud platforms, managing infrastructure-as-code.
• Enhance developer experience by creating tools and portals for job submission and metrics analysis.
• Enforce security and compliance policies for data access and container hardening.
• Collaborate cross-functionally with data, model, and product teams to align infrastructure roadmaps.

• 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.