Senior Software Engineer – AI Engineering

at  Microsoft

Join us in building a transformative research knowledge reasoning platform based on state-of-the-art large language & vision models (LLMs). Our agile and independent team is on a mission to revolutionize & democratize data analysis and research insight by transforming complex, time-consuming text reasoning tasks into efficient and trustable processes. You’ll help us build a next generation platform.
As a Senior Software Engineer- Artificial Intelligence (AI) Engineering on our team, you will play a crucial role in building and measuring the advanced AI capabilities in the platform. You will work on developing and optimizing algorithms and pipelines that transform qualitative data into actionable insights and data structures. You’ll invent and optimize novel Retrieval Augmented Generation (RAG) patterns at large scale with graph databases, and measure and fine tune the reliability of the system.
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.

REQUIRED QUALIFICATIONS:

• Bachelor’s Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.
• OR equivalent experience.

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 Cloud background check upon hire/transfer and every two years thereafter.

ADDITIONAL / PREFERRED QUALIFICATIONS:

• 2+ years experience building & deploying one or more of the following: recommendation systems, deep learning, machine learning, text analysis, information retrieval, NLP.
• Ability to oversee Machine Learning systems end-to-end - from data pipelines and training to real-time prediction engines.
• Experience with graph databases and NoSQL.
• Experience deploying, handling, and scaling infrastructure on Microsoft Azure platform.
• Experience partnering and working with cross-disciplinary teams.
  Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 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 for the role until June 12, 2024.
  Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations

• Collaborate closely with project managers, researchers, architects, and technical leads to understand and refine user requirements for Machine Learning (ML) systems and research knowledge reasoning. Incorporate customer feedback into future designs and solutions.
• Lead architecture discussions and contribute to the design of scalable AI systems for data analysis, storage, and retrieval. Develop comprehensive design documents.
• Develop, optimize, and review code to ensure extensibility, maintainability, and adherence to best practices.
• Integrate telemetry data collection to monitor AI behavior, performance, and reliability. Use this data to refine product design and improve engineering decisions, ensuring continuous improvement in product quality.
• Proactively remain current in skills by investing time and effort into staying abrest of industry and academic advances and incorporating into our technology.
• Embody our Culture and Values.