Principal Applied Scientist

What you'll do

• Build runtime AI automation for infrastructure capacity and health, including anomaly detection, root-cause analysis, and mitigation.
• Develop forecasting, machine-learning, and mathematical optimization systems to improve capacity, reliability, and service performance.
• Set technical direction and take research and prototypes into production in partnership with engineering, product, and research teams.

What they ask for

• Degree and related experience: bachelor's plus 6+ years, master's plus 4+ years, doctorate plus 2+ years, or equivalent experience; additional principal-level pathways are master's plus 9+ years, doctorate plus 6+ years, or equivalent experience.
• 5+ years creating publications; 2+ years presenting as an invited speaker; and 5+ years conducting research as part of a research program.
• 3+ years developing and deploying live production systems on a product team, and 3+ years working across product-cycle stages from ideation to shipping.
• Experience building ML or AI solutions in Python, C#, C++, or R with modern ML frameworks or LLM tools; working knowledge of SQL or a similar query language.

Nice to have

• Experience building LLM-powered applications and agentic systems, including tool use, retrieval-augmented generation, multi-agent orchestration, and production evaluation.
• Experience with anomaly detection, root-cause analysis, AIOps, incident mitigation, time-series forecasting, production ML systems, large-scale data platforms, or mathematical optimization.

Pay

USD $142,800 - $274,800 per year (base salary); USD $188,000 - $304,200 per year (base salary)

Tools

Python, C#, C++, R, PyTorch, scikit-learn, SQL, Microsoft Agent Framework

AI focus

Develop production AI systems for infrastructure capacity and health, including agentic automation, anomaly detection, root-cause analysis, automated mitigation, forecasting, and optimization.