Principal Applied Scientist
£74.7k - £161.8k/yr
Expert
Bachelor's, Master's, PhD
London, UK
In Person
AI & Machine LearningApplied Machine Learning
About the job
Requirements
- A bachelor's, master's, or doctorate degree in Statistics, Econometrics, Computer Science, Electrical Engineering, Computer Engineering, or a related field, plus related experience in areas such as statistics, predictive analytics, or research; equivalent experience is accepted.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Responsibilities
- Design and run experiments, define offline and online evaluation metrics, and develop scalable retrieval pipelines and models for enterprise-scale search systems.
- Advance semantic retrieval using late-interaction architectures such as ColBERT; dense retrieval and embedding model fine-tuning; modern lexical retrieval approaches such as SPLADE; hybrid retrieval combining dense and sparse retrieval; query understanding and representation learning; multi-stage ranking and retrieval optimization; retrieval-augmented generation; personalization and contextual ranking; knowledge retrieval for agentic AI systems; reinforcement learning and reasoning-aware retrieval systems; and LLM-integrated retrieval architectures.
- Apply best practices in Responsible AI, privacy-preserving machine learning, and scalability for production-grade enterprise systems.
- Partner with Engineering, Product Management, and Design to translate product requirements and research advances into scalable and reliable retrieval infrastructure for Copilot Search, Chat, and Agent experiences.
- Work with Microsoft Research, Azure AI platform teams, and product organizations to bring retrieval and ranking advances into large-scale production systems.
- Understand user retrieval pain points and enterprise grounding challenges, and develop solutions that improve relevance, answer quality, freshness, and personalization.
- Provide technical leadership and mentorship to scientists and engineers working on retrieval, ranking, and recommendation systems; help establish best practices and contribute to the broader retrieval science strategy across CACore.
- Establish and evolve evaluation frameworks and success metrics for retrieval quality, grounding relevance, ranking effectiveness, and downstream Copilot quality metrics.
- Keep up with advances in retrieval and ranking research, including semantic retrieval, sparse retrieval, retrieval-augmented generation systems, and LLM-grounded search.
Desired Qualifications
- Hands-on experience developing retrieval or ranking systems at production scale.
- Demonstrated expertise in one or more of semantic retrieval, dense retrieval systems, embedding model training or fine-tuning, SPLADE or sparse retrieval methods, hybrid retrieval architectures, ranking systems for search or recommendation, and large-scale information retrieval systems.
- Experience developing machine-learning systems in Python and modern machine-learning frameworks such as PyTorch.
- Experience evaluating retrieval quality using offline metrics and/or online experimentation.
- Experience developing retrieval systems for retrieval-augmented generation or agentic AI architectures.
- Publications in top-tier conferences such as SIGIR, RecSys, KDD, WWW, WSDM, ACL, or EMNLP.
- Experience shipping retrieval systems integrated with LLM-based products.
- Familiarity with enterprise search, personalization, and recommendation systems.
- Experience optimizing retrieval latency, scalability, and serving infrastructure.
- Experience with reinforcement learning or retrieval-aware reasoning systems.
About the company
Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.
Company Size
10,001+
Company Stage
IPO
Headquarters
Redmond, Washington
Founded
1975
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Simplify's Take
What believers are saying
- US corporate staff receive education support: eligible, approved graduate coursework qualifies for up to $10,000 annually.
- Cloud demand expands: July 2026 results showed Azure and other cloud services revenue grew 43% year-over-year in fiscal Q4.
- Investment has an earnings cushion: July 2026 results reported $155.2 billion consolidated operating profit for fiscal 2026.
What critics are saying
- Performance reviews include security: every Microsoft employee must discuss their security contribution with their manager.
- Office flexibility depends on the role: Microsoft's postings specify requirements ranging from fully remote to fully on-site.
- Cloud capacity faces local limits: Microsoft describes power-grid delays and water constraints affecting US datacenter expansion.
What makes Microsoft unique
- Hybrid customers stay within reach: Azure Arc manages servers across customer datacenters and competing clouds.
- Developer reach extends beyond Azure: Microsoft's GitHub hosts code collaboration alongside AI coding tools.
- Professional data widens its business: Microsoft owns LinkedIn's recruiting, advertising and workplace-learning network.
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Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- 401(k) Company Match
- Professional Development Budget
- Conference Attendance Budget
- Flexible Work Hours
- Remote Work Options