Senior​/ML Scientist - Bidding & Optimization; f​/m​/d

adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world’s smartphones
, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem.

Next-Gen Machine Intelligence for Auctions & Real-Time Bidding

The Data Science Research team builds the foundational algorithms that govern real-time bidding, budget pacing, and allocation mechanics across our products. Operating as a horizontal deep-tech layer, the team leverages advanced AI—specifically reinforcement learning, objective-based optimization, and control theory—to deliver critical systems that perfectly harmonize advertiser ROI, platform health, and user relevance. These frameworks scale adjoe’s products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users
.

The team operates at the intersection of high-load, low-latency engineering, auction mechanism design, and state-of-the-art machine learning
. Acting as the company’s internal science bar raiser, they translate complex business constraints into mathematical objectives. The stack is optimized for high throughput:
PyTorch for training deep learning and RL models, distributed architectures for large-scale Bayesian inference, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure. The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain ultra-low latency, real-time production environments evaluating tens of thousands of requests per second.

• PhD or equivalent research depth, with a production track record. You have a PhD in CS, Statistics, Math, or Physics (or an MSc with extensive industry research) and a track record of peer-reviewed publications in fields like Computational Advertising, Auction Theory, Mechanism Design, or Game Theory. You’ve spent 4+ years optimizing complex systems through automated algorithms in AdTech, marketplaces, or high-frequency trading.

• You translate research into production, not just prototypes. You distill SOTA research into robust, production-ready code optimized for sub-millisecond latency. At adjoe, that means architecting sophisticated auction mechanics, real-time bidding engines, and allocation algorithms serving millions of requests across a stack built on 770 million users.

• Deep expertise in Reinforcement Learning and Optimization. You have hands‑on, deep theoretical and technical expertise in objective‑based optimization, control theory, or RL applied specifically to bidding, pricing strategy, and budget pacing under extreme production constraints.

• Mastering high-dimensional data at scale. Large-scale Bayesian inference and handling sparse, high-dimensional advertising data are core to your work. You are strongly proficient in Python and related stacks, and know exactly how to architect scalable data pipelines to feed real-time optimization models.

• Raises the technical bar around them. You lead architectural debates, collaborate tightly with Product Managers and Engineers to map business goals to mathematical objective functions, mentor junior scientists, and drive the team’s research direction without needing a roadmap handed to you.