Senior Applied Scientist (AI)

TL;DR

Senior Applied Scientist (AI): Building core intelligence for ad interaction prediction using transformer-based models with an accent on large-scale ML systems and noisy feedback handling. Focus on developing estimated conversion models, designing weak-label generation pipelines, and optimizing ad ranking and bidding at web scale.

Location: Redmond, United States. Must be based in or able to commute to the office at least four days per week.

Salary: $119,800 – $234,700 per year

Company

hirify.global's Monetization team develops high-parameter transformer models to power ad ranking, pricing, and optimization across global consumer surfaces.

What you will do

• Drive modeling and data innovations for predicting ad interaction outcomes under partial and noisy feedback.
• Build estimated conversion models and design data-driven attribution and weak-label generation pipelines.
• Develop robust learning and calibration methods for scenarios with sparse, delayed, or unobservable outcomes.
• Design and evaluate multi-task and proxy-signal models to enhance measurement frameworks.
• Translate modeling advancements into production-ready systems that impact ad ranking, bidding, and advertiser ROI.

Requirements

• Bachelor's degree in Statistics, CS, EE, or related field with 4+ years of experience (or Master's + 3 years / PhD + 1 year).
• Strong hands-on experience with modern ML models (Deep Learning, Tree-based, or Linear) and feature engineering.
• Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow.
• Experience building and shipping ML models in production using large-scale real-world data.
• Solid understanding of supervised learning, multi-task learning, offline evaluation, and A/B testing.
• Must be located within a 50-mile commute of the Redmond office to meet the 4-day-per-week in-office requirement.

Nice to have

• Experience with academic publications, patents, or presenting as an invited speaker at industry conferences.
• Background in causal inference, attribution, or counterfactual evaluation.
• Experience with large-scale online marketplaces or recommendation systems.
• Proven technical leadership in cross-team modeling efforts or platform-level ML systems.

Culture & Benefits

• Environment based on a growth mindset, innovation, and a culture of inclusion.
• Core values of respect, integrity, and accountability.
• Comprehensive corporate benefits package including health and retirement options.