Principal Applied Scientist (AI)

TL;DR

Principal Applied Scientist (AI/RecSys): Leading the science behind the ranking and content-quality stack for Copilot Discover with an accent on LLMs, multimodal models, and large-scale recommender systems. Focus on architecting DNN-enhanced recommenders, reducing misinformation/toxicity error rates, and ensuring system safety and integrity.

Location: Redmond, United States. Employees within a 50-mile commute of the office are expected to work from the office at least four days per week.

Salary: $142,800 – $274,800 per year (typical US range)

Company

hirify.global is building the next generation of AI-powered quality understanding and recommendation systems to surface relevant and trustworthy content across Microsoft surfaces.

What you will do

• Lead content-quality understanding at scale by designing models to assess credibility, usefulness, and safety across multiple modalities.
• Architect and productionize large-scale DNN/LLM-enhanced recommenders using representation learning, sequence modeling, and slate optimization.
• Define offline metrics (NDCG, ERR) and online methodologies (A/B tests, bandits) to evaluate model impact.
• Encode safety standards and editorial principles into the ML system through red-teaming and adversarial safeguard layers.
• Collaborate with engineering on data contracts, feature stores, distributed training, and automated rollout pipelines.
• Provide technical leadership and mentor a high-caliber science cohort through design reviews and knowledge sharing.

Requirements

• Degree in Statistics, Computer Science, Electrical/Computer Engineering, or related field.
• Experience requirement: 6+ years with a Bachelor's, 4+ years with a Master's, or 3+ years with a PhD in predictive analytics or research.
• Must be based in or able to work from the Redmond office (minimum 4 days per week).
• Expertise with LLMs (prompting, finetuning, RAG), multimodal modeling, and retrieval-augmented recommendation.
• Proficiency in Python and at least one major deep learning framework (PyTorch or TensorFlow).
• 2+ years of experience with consumer-scale recommender systems or content-quality/safety models.

Nice to have

• Publications at top AI/ML conferences (e.g., KDD, SIGIR, NeurIPS, ICML, RecSys).
• Familiarity with the Microsoft stack (Azure ML, Kusto, Synapse, Azure AI Foundry).
• Experience with counterfactual learning and multi-objective optimization.

Culture & Benefits

• Inclusive culture based on respect, integrity, and accountability.
• Environment promoting a growth mindset and innovation to empower others.
• Comprehensive corporate benefits package.