Sr. Machine Learning Engineer, Applied Scientist

AdTech - Senior Machine Learning Engineer | Applied Research

The Opportunity

This role sits at the intersection of Machine Learning Engineering and Applied Research. You will work on complex modeling problems where traditional approaches often fail. The work involves deep analytical reasoning, experimentation, and creative modeling approaches that push beyond standard ML implementations.

Your models will operate inside a real-time bidding system processing millions of ad opportunities per second, where small improvements in prediction accuracy directly translate into significant revenue impact.

What You’ll Work On

Core Modeling Systems

• Conversion prediction models (probability of install or action given an impression)
• Lifetime value (LTV) prediction models for post-install behavior
• Systems that combine multiple estimators to determine real-time bid values

Advanced Modeling Challenges

• Handling extreme class imbalance in user conversion events
• Solving delayed attribution and incomplete labeling
• Designing models robust to noisy attribution signals
• Reducing bias introduced by first-party data limitations
• Improving performance across new inventory and cold-start users

Example Problems You May Solve

• Designing model architectures to reduce bias between first-party and third-party training datasets
• Developing multi-model approaches that separate conversion prediction from attribution prediction
• Creating new training strategies for sparse, delayed signals in large-scale datasets
• Improving prediction performance in emerging channels such as Connected TV (CTV)

Responsibilities

• Own the end-to-end applied research lifecycle, from hypothesis generation to production deployment
• Develop and optimize large-scale ML models used in real-time bidding systems
• Conduct offline experiments and design rigorous A/B testing frameworks
• Analyze results deeply to identify performance drivers and optimization opportunities
• Collaborate with engineering, data infrastructure, and operations teams to productionize models
• Contribute to architectural decisions across the ML platform

What We’re Looking For

Required

• 3–6+ years of industry experience in Machine Learning, Applied AI, or Predictive Modeling
• Strong coding skills in Python (Scala or Java a plus)
• Solid SQL and large-scale data analysis experience
• Experience designing experiments and interpreting statistical results
• Strong analytical thinking and ability to solve complex, ambiguous problems

Preferred

• Experience in AdTech, DSPs, recommendation systems, or real-time bidding
• Background working at companies like Google, Meta, Amazon, AppLovin, Moloco, Liftoff, etc.
• Experience with large-scale ML systems or recommender models
• Knowledge of deep learning architectures, transformers, or sequence models
• Advanced degree (MS or PhD) in ML, Statistics, Applied Mathematics, or Computer Science