Senior Applied Scientist (AI)

TL;DR

Senior Applied Scientist (AI): Building transformer-based models that predict ad interactions and outcomes with an accent on reasoning over long user histories, sparse signals, and heterogeneous events. Focus on designing multi-task learning systems, attribution pipelines, and robust evaluation frameworks for production-scale ad ranking and optimization.

Location: Redmond, United States. Employees within 50-mile commute expected to work from office at least four days per week starting January 26, 2026.

Salary: USD $119,800 – $234,700 per year (USD $160,200 – $261,000 in San Francisco Bay area and New York City).

Company

hirify.global AI team building core intelligence for ad ranking, pricing, and optimization across large-scale consumer surfaces.

What you will do

• Drive modeling and data innovations for ad interaction outcome prediction under partial and noisy feedback.
• Build estimated conversion models, data-driven attribution and weak-label generation pipelines.
• Develop robust learning and calibration methods for sparse, delayed, or unobservable user outcomes.
• Design and evaluate multi-task and proxy-signal models.
• Improve offline and online measurement frameworks.
• Translate modeling advances into production-ready systems impacting ad ranking, bidding, ROI, and user experience.

Requirements

• Bachelor’s in Statistics, Econometrics, CS, EE/CE or related + 4+ years experience OR Master’s + 3+ years OR Doctorate + 1+ year OR equivalent.
• Experience in statistics, predictive analytics, or research.
• Solid programming in Python and ML frameworks (PyTorch/TensorFlow).
• Hands-on with modern ML models, feature engineering, supervised/multi-task learning.
• Experience with large-scale data pipelines, offline evaluation, A/B experimentation.
• Ability to drive projects from definition to production.

Nice to have

• Master’s/Doctorate + 6+/3+ years experience.
• 3+ years publications, conference presentations, research programs.
• 1+ year deploying production ML systems/products.
• Experience with noisy/weak labels, conversion/attribution modeling, model calibration.
• Background in causal inference, large-scale ads/marketplaces, multi-task systems.
• 4+ years shipping production ML models, technical leadership.

Culture & Benefits

• Growth mindset, innovation, collaboration on values of respect, integrity, accountability.
• Culture of inclusion where everyone can thrive.
• Potential benefits and other compensation (details on careers site).