Principal Applied Scientist

Posted 23 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Leads applied research for enterprise retrieval, ranking, grounding, knowledge representation, evaluation, and autonomous AI workflows. Develops multi-hop retrieval, semantic enrichment, knowledge graphs, agent memory, trust-aware authorization, and knowledge acquisition systems. Partners with engineering and product teams to productionize scientific innovations at hyperscale. The role requires translating machine learning research into enterprise AI systems and influencing platform architecture and cross-team roadmaps.
Summary Generated by Built In
Overview

Copilot Connectors Service transforms enterprise knowledge from systems such as ServiceNow, Salesforce, Azure DevOps, Jira, Confluence GitHub, and other business-critical applications into first-class knowledge within the Microsoft ecosystem. This knowledge powers Microsoft 365 Copilot, Cowork, Autopilot, WorkIQ, GitHub CLI, and future AI experiences by making external content, permissions, relationships, and business context available as trusted, AI-ready enterprise knowledge. This allows customers to manage knowledge and automations that cuts across many system of records and workflow system right in Microsoft Copilot.

Copilot Connectors team works across the stack, from crawl systems, data modelling, information extraction, indexing, query and retrieval, integrations into different hardness system, writing skills and plug-ins and hill climbing by building Eval systems.  We manage a large footprint of connectors and our building set of agents which help us manage and scale the Connectors ecosystem. As a Principal Applied Scientist, you will work closely with leadership to define the scientific foundations for enterprise retrieval, grounding, evaluation, and agent-ready knowledge systems and automations that power the next generation of Microsoft AI experiences.


Responsibilities
  • Drive innovation in enterprise retrieval,, ranking, grounding, and knowledge representation and autonomous workflows for AI agents and next-generation Microsoft AI experiences.
  • Advance retrieval quality science through SEVALs, evaluation frameworks, and metrics for Recall@K, grounding quality, citation correctness, freshness, coverage, and task success.
  • Develop techniques for multi-hop retrieval, cross-source reasoning, semantic enrichment, knowledge graphs, and agent memory.
  • Build trust-aware AI systems that respect enterprise permissions, provenance, and authorization.
  • Pioneer autonomous knowledge acquisition, including relationship discovery, metadata inference, summarization, and knowledge graph generation.
  • Partner with engineering and product teams to bring scientific innovations into production at hyperscale.

Qualifications

Required/Minimum Qualifications:

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research).
    • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research).
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).
    • OR equivalent experience.
  • Proven track record of translating research into large-scale production systems.

Additional or preferred qualifications

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. 

Preferred Qualifications:

  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) - OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) - OR equivalent experience.
  • 8+ years of experience across ML with a proven record for applying ML across production systems.
  • Experience with enterprise AI, retrieval systems, agent architectures, or knowledge platforms, evals.
  • Experience building evaluation frameworks and quality metrics for Agentic systems.
  • Experience in enterprise space.
  • Proven ability to influence platform architecture and align cross-team roadmaps.

Why Join Us

The industry is moving beyond search and chat experiences toward AI agents that can understand, reason over, and act on enterprise knowledge. This role offers a unique opportunity to define how trusted enterprise knowledge powers Copilot, Cowork, Autopilot, WorkIQ, GitHub CLI, and future AI experiences across Microsoft.


#CAPIDC

#M365CORE


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Skills Required

  • Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 6 or more years of related experience
  • Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 4 or more years of related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 3 or more years of related experience
  • Equivalent experience may substitute for the stated education and experience requirements
  • Proven track record of translating research into large-scale production systems
  • Ability to pass the Microsoft Cloud background check and applicable customer or government security screenings
  • Master's degree in a relevant field plus 6 or more years of related experience
  • Doctorate in a relevant field plus 5 or more years of related experience
  • 8 or more years of experience applying machine learning across production systems
  • Experience with enterprise AI, retrieval systems, agent architectures, knowledge platforms, or evaluation systems
  • Experience building evaluation frameworks and quality metrics for agentic systems
  • Enterprise experience
  • Ability to influence platform architecture and align cross-team roadmaps

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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The Company
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Year Founded: 1975

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