Applied Machine Learning Research 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, Natural Language Processing (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.

We are seeking an enthusiastic Applied Machine Learning Research Engineer who is passionate about the latest AI advancements and is willing to take on variety of challenges - from coding to UX development, model building, prompt engineering, building advanced agentic solutions - to join our dynamic team.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. 

Responsibilities

• Design, develop, and run advanced AI/ML systems.
• Facilitate deployment of advanced AI solutions by designing and implementing infrastructure components
• Create and implement machine learning models and algorithms to solve business problems.
• Collaborate with cross-functional teams to design and implement data-driven solutions.
• Collect, synthetize, clean, and organize large datasets from multiple sources, perform large scale analysis and interpret complex data to identify patterns, trends, and insights that can inform business decisions.
• Develop, refine, and optimize AI-generated text prompts for accuracy, engagement, and relevance across various applications.
• Design end-to-end ML experiments and tests on large, structured and unstructured data sets.
• Stay up to date with the latest trends and techniques in data science, machine learning, prompt engineering and automation.
• Embody our culture and values 

Qualifications

Required Qualifications 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience 
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) 
  • OR equivalent experience. 
• Skilled in problem solving and programming (Python, C#); skilled with using big data tools and scripting languages (SQL, PySpark, KQL)
• 1+ years of professional experience in a technical role building and deploying ML solutions at scale for real-world problems
• Proficiency in using statistical/analysis/ML tools, defining, and implementing intelligent solutions on data.
• Proficient understanding of Large Language Models (LLMs) Agents, Prompt Engineering, Data Mining, and equivalent work experience

Preferred Qualifications 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) 
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) 
  • Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) 
  • OR equivalent experience. 
• Experience with deep learning/LLMs applied to areas such as graph learning, IR, NLP, computer vision, etc., is preferred.
• Solid cross-group and interpersonal skills, with the ability to articulate solutions.
• Experience in government regulations, business compliance, business processes in enterprises, legal discovery, etc.

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.

• • Experience in government regulations, business compliance, business processes in enterprises, legal discovery, etc.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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