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Senior Applied Scientist

Microsoft
London, GBR
Full-time
Senior · 2+ years experience
Hybrid
GBP 74700-161800 yearly / year
Discovered Yesterday
PythonPyTorchSPLADE

Full Job Posting

Advance Retrieval Science

Design and run experiments, define offline and online evaluation metrics, and develop scalable retrieval pipelines and models for enterprise-scale search systems.

Areas of focus include

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 systems combining dense + sparse retrieval

Query understanding and representation learning

Multi-stage ranking and retrieval optimisation

Retrieval-augmented generation (RAG)

Personalization and contextual ranking

Knowledge retrieval for agentic AI systems

Reinforcement learning and reasoning-aware retrieval systems

LLM-integrated retrieval architectures

You will apply best practices in Responsible AI, Privacy-Preserving ML, and scalability for production-grade enterprise systems.

Drive Product Innovation

Partner with Engineering, PM and Design to translate product requirements and research advances into scalable and reliable retrieval infrastructure supporting Copilot Search, Chat and Agent experiences.

Collaborate Across Microsoft

Work closely with Microsoft Research, Azure AI platform teams and product organizations to bring cutting-edge retrieval and ranking advances into large-scale production systems.

Champion Customer Impact

Deeply understand user retrieval pain points and enterprise grounding challenges, and develop solutions that materially improve relevance, answer quality, freshness and personalization.

Lead and Mentor

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.

Define Success

Establish and evolve evaluation frameworks and success metrics for retrieval quality, grounding relevance, ranking effectiveness and downstream Copilot quality metrics.

Stay Ahead

Keep up with the latest advances in retrieval and ranking research, including developments in semantic retrieval, sparse retrieval, RAG systems and LLM-grounded search. Publishing at top-tier venues such as SIGIR, RecSys, WSDM, KDD, ACL and EMNLP is encouraged.

Required Qualifications

  • Bachelor's, Masters, or Doctorate Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics predictive analytics, research), 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.

Preferred Qualifications

  • Solid hands-on experience developing retrieval or ranking systems at production scale.
  • Demonstrated expertise in one or more of the following: 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 Large-scale information retrieval systems
  • 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
  • Large-scale information retrieval systems
  • Experience developing ML systems in Python and modern ML frameworks such as PyTorch.
  • Experience evaluating retrieval quality using offline metrics and/or online experimentation.
  • Experience developing retrieval systems for RAG 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.
  • #CAP #Copilot
  • Applied Sciences IC4 - The typical base pay range for this role across United Kingdom is £ 74,700.00 - £ 122,600.00 per year. Certain roles may be eligible for benefits and other compensation.
  • Find additional benefits and pay information here: https://careers.microsoft.com/v2/global/en/corporate-pay/united-kingdom-corporate-pay.html
  • Applied Sciences IC5 - The typical base pay range for this role across United Kingdom is £ 93,500.00 - £ 161,800.00 per year. Certain roles may be eligible for benefits and other compensation.
  • 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.

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