Microsoft Applied Scientist II 

India, Karnataka, Bengaluru 

857483956

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
  • OR equivalent experience.
• Experience with large-scale models and frameworks such as PyTorch.
• Experience building, deploying, and optimizing large-scale AI/ML models in real-world applications, especially in NLP, Information Retrieval, or Computer Vision.
• Publications in top-tier conferences like NeurIPS, ICML, CVPR, SIGIR, KDD, ACL, EMNLP, ICLR, WWW, WSDM or similar, demonstrating expertise in advancing the field.

Other Requirements:

Candidates must be able to meet Microsoft, customer and/or government security screening requirements that 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.

Additional or Preferred Qualifications:

• PhD in Machine Learning, AI, or related fields.
• Experience working with large language models / multi-billion parameter models, focusing on their efficient training and online inference.
• Background in developing or modifying deep learning algorithms/architectures to improve computational and memory efficiency.
• Experience in online advertising, search engines, or recommendation systems.
  

• Drive AI innovation: Lead the development of cutting-edge models that select and rank ads, predict user interaction, and optimize advertiser outcomes. You will leverage and advance Deep Learning, Reinforcement Learning, Causal Inference, and other techniques to solve complex problems.
• Optimize at scale: Design, build, and deploy models that operate at web scale, ensuring they are robust, scalable, and high performing in real-world settings. You will directly improve user engagement, ad relevance, and advertiser return on.
• Perform large-scale online and offline experiments to continuously optimize and validate model performance, ensuring real-time impact on user and advertiser experiences.
• Work closely with worldwide research, engineers, data scientists, and product teams to integrate your solutions into Microsoft Ads systems, driving cross-team collaboration and delivering impactful end-to-end solutions.