Senior Applied Scientist

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence

In short

The CASQ Search Relevance team is seeking a Senior Applied Scientist to drive innovative machine learning and information retrieval solutions for Copilot Search, Bizchat, and other Microsoft search experiences. This role involves applying state-of-the-art techniques in retrieval, ranking, and LLMs, with opportunities for technical leadership and team mentorship.

Responsibilities

Drive end-to-end applied science projects from ideation to shipping.
Lead high-impact projects improving Copilot Chat, Copilot Search, and BizChat experiences.
Identify search and relevance gaps, formulate hypotheses, and deliver scalable solutions.
Inspire, mentor, and empower a team of applied scientists.
Guide day-to-day work, ensure scientific and engineering rigor, and be accountable for team output.
Invent and apply cutting-edge techniques in ML, NLP, and information retrieval.
Design novel approaches for retrieval, ranking, query understanding, and semantic search.
Document, share, and amplify learnings through experimental results and internal publications.
Translate business goals into scientific strategy and partner with product stakeholders.
Collaborate cross-functionally with engineering, science, and product teams across time zones.
Embody Microsoft's Culture and Values.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience OR Master's Degree AND 3+ years related experience OR Doctorate AND 1+ year(s) related experience OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements.
Microsoft Cloud Background Check required.

Desired Qualifications

Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience OR Doctorate AND 6+ years related experience OR equivalent experience.
5+ years experience in applied science projects from ideation to production in high-scale environments (search, recommendation, conversational AI).
5+ years experience in data analysis at scale (logs, telemetry, large datasets).
6+ years experience creating publications (patents, libraries, peer-reviewed academic papers).
2+ years experience presenting at conferences or other events.
5+ years experience conducting research as part of a research program.
5+ years experience developing and deploying live production systems.
5+ years experience developing and deploying products/systems at multiple points in the product cycle.
Experience in search and ranking systems, semantic retrieval, and information retrieval at scale.
Applied experience with state-of-the-art sparse and dense retrieval and ranking techniques.
Experience with RAG architectures using LLMs (e.g., OpenAI GPT, T5, Llama).
Experience with Fine-tuning or prompt engineering of large-scale language models.
Familiarity with hybrid search strategies, LTR frameworks, and evaluation methodologies for IR systems (offline metrics, A/B testing, relevance judgments).

Benefits

USD $119,800 - $234,700 per year (US average base pay range).
USD $160,200 - $261,000 per year (San Francisco Bay area and New York City metropolitan area).
Certain roles may be eligible for benefits and other compensation.
Applications accepted on an ongoing basis until the position is filled.
Position open for a minimum of 5 days.

Skills

Machine LearningInformation RetrievalLarge Language ModelsRAGFAISSANNScaNNTransformerNatural Language ProcessingVector SearchLearning-to-rankA/B testingOpenAI GPTT5Llama

#AI#Machine Learning#Information Retrieval#Search Relevance#LLM#RAG#Copilot

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