About this role
Microsoft Ads seeks a Principal Applied Scientist to advance ad retrieval, matching, ranking, and generation at web scale. The role combines research with production delivery to improve user experience, advertiser return on investment, and platform efficiency.
Responsibilities
- Develop retrieval, ranking, matching, and generative models; train, fine-tune, align, and productionize small language models, large language models, and large reasoning models.
- Improve the Ads ranking platform’s usability, reliability, scalability, efficiency, and architectural coherence. Ship solutions, measure their impact, and iterate on results.
- Set technical direction, coach a distributed team, influence cross-organization strategy, follow AI research, and collaborate with research and engineering teams.
Required qualifications
A bachelor’s degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field with 6+ years of related experience; a master’s with 4+ years; a doctorate with 3+ years; or equivalent experience. Related experience may include statistics, predictive analytics, or research. The hire must meet applicable Microsoft, customer, or government security-screening requirements, including a Microsoft Cloud background check upon hire or transfer and every two years thereafter.
Preferred qualifications
A relevant master’s degree with 6+ years of related experience, a doctorate with 5+ years, or equivalent experience; 8+ years in machine learning with a record of shipping large-scale models; expertise in training and inference optimization; and experience influencing platform architecture and cross-team roadmaps. Also preferred are publications at venues such as NeurIPS, ICML, KDD, WWW, ACL, or SIGIR; hands-on SLM, LLM, or LRM training, fine-tuning, and post-training; experience scaling recommendation systems with massive query/item spaces and multi-stage ranking pipelines; and proficiency with PyTorch, Hugging Face, TensorFlow, and distributed training on large datasets.
Location and arrangement: Bangalore, Karnataka, India; four days per week in-office, with less than 25% travel. This is a full-time individual-contributor role.