Principal Applied AI Scientist

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.

Welcome to the applied research arm of Microsoft Security AI (Artificial Intelligence), where we engage in research to create truly differentiating products and services across Microsoft’s Security Division. In the 18 months since our organization’s founding, we have driven the research behind Microsoft Security Copilot and a suite of both foundational and specialized AI models. Our project portfolio includes a variety of short-to-long-term horizon projects with applications across Microsoft security suite. We are a culture-first organization, and our culture is one of ambition and science together with curiosity and humility. We believe in a future that is brighter and better than the present, and we want to be the ones who make it happen. We believe that customer obsession requires a commitment to investing in new knowledge. Our people are some of the best and brightest scientists and engineers in the world, and we collaborate every day, helping each other grow and break boundaries. But we do this with the humility that comes with the immense challenges of providing cybersecurity to millions of customers. We oversee and coordinate AI investments for Microsoft Security; work with engineering partners to accelerate and scale security research by making AI tools and data more accessible to security researchers; serve as Microsoft Security’s central hub for industry and academic partnerships; and drive thought leadership efforts to let the world know about our trailblazing work in security science and AI. We are looking for a "Principal Applied AI Scientist" to join a newly created team to reshape how we defend Microsoft using autonomous agents.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. 

Business Understanding and Impact

• Leverages subject matter expertise to analyze problems and issues facing projects to uncover, manage, and/or mitigate factors that can influence final outcomes across product lines. Partners with business team to drive strategy and recommend improvements.
• Raises opportunities to look for new work opportunities and different contexts to use existing work.
• Establishes, applies, and teaches standards and best practices. Data Preparation and Understanding
• Oversees data acquisition efforts and ensures data is properly formatted and accurately described.
• Utilizes key technologies and tools necessary for data exploration (e.g., structured query language [SQL], Python).
• Uses querying, visualization, and reporting techniques to explore the data, including distribution of key attributes, relationships between attributes, simple aggregations, properties of significant sub-populations, and statistical analyses.
• Mentors and coaches engineers in data cleaning and analysis best practices. Identifies gaps in current data sets and drives onboarding of new data sets.
• Drives discussions around ethics and privacy policies related to collecting and preparing data.
• Integrates industry-wide ethics insights and best practices to influence internal processes and drive decision-making.
• Builds data platforms from scratch across products Identifies new opportunities from data and processes data in a way that is usable for general purpose.
• Actively contributes to the body of thought leadership and intellectual property (IP) on best practices for data acquisition and understanding. Leads and resolves data-integrity problems.
• Modeling and Statistical Analysis Generalizes machine learning (ML) solutions into repeatable frameworks (e.g., modules, packages, general-purpose software) for others to use.
• Exemplifies and enforces team standards related to bias, privacy, and ethics.
• Evaluates the methodology and performance of teammates’ models and, as appropriate, recommends solutions for improvement.
• Anticipates the risks of data leakage, the bias/variance tradeoff, methodological limitations, etc., and is able to guide teammates on solutions.
• Drives best practices relative to model validation, implementation, and application.
• Develops operational models that run at scale.
• Partners with others to identify and explore opportunities for the application of ML and predictive analysis.
• Identifies new customer opportunities for driving transformative customer solutions with ML modeling.
• Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics.
• Develops deep expertise in specialized areas by staying abreast of current and emerging methodologies an AI and ML.
• Evaluation Conducts thorough review of data analysis and modeling techniques used to summarize the process review and highlight areas that have been missed or need reexamining.
• Utilizes results of the assessment and process review to decide on next steps (e.g., deployment, further iterations, new projects).
• Identifies new evaluation approaches and metrics and invents new methodologies to evaluate models.

Industry and Research Knowledge/Opportunity

• Identification Tracks advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions.
• Researches and maintains deep knowledge of industry trends, technologies, and advances. Leverages knowledge of work being done on team to propose collaboration efforts.
• Proactively develops strategic responses to specific market strengths, weaknesses, opportunities, threats, and/or trends.
• Mentors and coaches less experienced engineers in data analysis best practices.
• Serves as subject matter expert and role model for less experienced engineers.
• Identifies strategy opportunities.
• Actively contributes to the body of thought leadership and intellectual property (IP) best practices by active
  
  
  
• Embody our culture and values.