Data Flywheel Infrastructure Engineer (AI)

Location: London, United Kingdom or Zurich, Switzerland. Starting January 26, 2026, employees located within 50 miles of a U.S. office or 25 miles of a non-U.S. office are expected to work from that office at least four days per week, subject to local law.

Salary: £74,700–£122,600 per year for IC4, or £93,500–£161,800 per year for IC5, across the United Kingdom.

Company

Microsoft AI's Superintelligence Team develops controllable, safety-aligned AI systems and partners with product teams to bring models to users.

What you will do

• Build scalable infrastructure for ingesting, processing, curating, versioning, and serving first-party and third-party data for pre-training and post-training.
• Implement governance, security, compliance, provenance, licensing, consent, access-control, retention, deletion, and audit capabilities in the data platform.
• Develop automated pipelines for classification, filtering, deduplication, quality scoring, semantic enrichment, and dataset construction.
• Convert model evaluations and failure signals into data tasks through failure clustering, hard-example mining, long-tail discovery, and targeted dataset generation.
• Build synthetic and AI-native data pipelines using LLMs, VLMs, and agents for generation, labeling, validation, enrichment, and transformation.
• Develop metrics and observability for dataset quality, coverage, diversity, contamination, duplication, policy compliance, and contribution to model capabilities.

Requirements

• Master's degree in computer science, mathematics, software engineering, computer engineering, or a related field with 3+ years of relevant experience; or bachelor's degree with 4+ years of relevant experience; or equivalent experience.
• Software engineering experience with Python, SQL, and Spark, Flink, or Ray.
• Experience in software development, data engineering, data science, data modeling, or business analytics.
• Ability to work from the London or Zurich location under the applicable office-attendance expectation.

Nice to have

• Experience building AI training-data governance platforms, including provenance, licensing, consent management, PII handling, policy enforcement, or auditable lineage.
• Experience with third-party datasets, licensed content, first-party product data, privacy-preserving processing, de-identification, confidential computing, or secure data collaboration.
• Experience with evaluation-to-data feedback loops, synthetic data, model graders, reward signals, hard-example mining, active learning, or data-mixture optimization.
• Experience with multimodal or agentic datasets and modern LLM training workflows, including pre-training, SFT, reinforcement learning, post-training, evaluation, and synthetic data.

Culture & Benefits

• Startup-like environment within Microsoft AI focused on frontier AI and human-centered superintelligence.
• Work with product teams whose models can reach a large global user base.
• Benefits and additional compensation may be available depending on the role.
• Microsoft is an equal opportunity employer and provides accommodation support during the application process.