Senior Applied AI Engineer

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.

Microsoft Purview's suite of products includes data security, insider risk management, legal eDiscovery, communication compliance, and data lifecycle management, supported by Copilot for Security innovations. The Data and Applied Sciences Research team leads the way in pioneering AI and machine learning innovations, specializing in deep learning, NLP, large language models (LLMs/GPT), graph models, AutoGPTs, chatbots, etc. Our research is dedicated to pushing the boundaries of technology, anticipating future needs, and seamlessly integrating AI innovations into our product suite. We aim to deliver groundbreaking solutions that not only address current demands but also establish the groundwork for transformative advancements in data and applied sciences.

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.

• Experience developing and deploying large scale AI applications and generative AI applications.
• Knowledge of machine learning algorithms and concepts (e.g., supervised learning, unsupervised learning, deep learning) as applied to generative AI.
• Familiarity with data science tools and techniques.
• 7+ years of professional experience in a technical role building and deploying ML solutions at scale for real-world problems
• Bachelors/Master’s degree with relevant course work toward Computer Science, Data Science, Statistics, Machine Learning, Data Mining, Prompt Engineering and equivalent work experience.
• Contributions to open-source generative AI projects.
• Excellent cross-group and interpersonal skills, with the ability to articulate solutions.
• Additional experience in any of the areas like cyber security, fraud detection, regulations, business processes in enterprises, legal discovery, etc., would be beneficial, but not mandatory.

Other Requirements
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

Microsoft Cloud Background Check:- This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

We are seeking an enthusiastic AI engineer who is passionate about the latest AI advancements, possesses a start-up mindset, and is willing to take on any challenge - from coding to UX development, model building, prompt engineering, and metric definition - to join our dynamic team.

Responsibilities include:

• Design, develop, and implement robust and scalable software applications that utilize generative AI techniques.
• Integrate LLMs and NLP into software solutions for tasks such as text generation, summarization, translation, and question answering.
• Optimize generative AI models and their performance for specific use cases.
• Develop NLP pipelines for tasks like text classification, sentiment analysis, and named entity recognition.
• Collaborate with AI researchers and data scientists to explore new applications of generative AI.
• Stay up-to-date with the latest trends and technologies in generative AI.