Our main Engineering challenges at our company
Build efficient and easy-to-use web products used by thousands of users working for the worlds most premium publishers, advertisers, and agencies.
Rich and diverse tech stack and system architecture to optimize for performance, scalability, resiliency, and cost efficiency. We use mostly Scala and TypeScript, among others.
Working in a very high-traffic environment (2.2 billion users per month, 100 billion events per day) with low latency and high availability constraints (2 million requests per second, responses in less than 150 milliseconds).
Management of large datasets with milliseconds order of magnitude access time, to compute in a near real-time complex auction resolution algorithm (18 million predictions per second).
A fast-changing environment where we continuously collaborate with Product teams and constantly adapt our Cloud infrastructure for new features and Products.
Bring a wide diversity of profiles to the same level of quality and knowledge
Work in an international environment with offices located in Israel, Slovenia and France.
About the opportunity
We are looking for a Senior Data Scientist to join a team of applied research.
The AI department currently consists of 50 people who are a mix of data scientists, machine learning and backend engineers.
The department provides technologies that power outcomes of campaigns with a total yearly turn over of $1.7B.
Runs large scale prediction and control systems for ad delivery, dealing with millions of live ads, doing more than a billion predictions per second based on large on-line trained models being updated every 5 minutes.
What will you do?
As a Senior Data Scientist, your mission will be to:
Innovate at Scale: Stay at the forefront of AdTech research, focusing on CTR prediction, online learning regimes, and high-dimensional embeddings.
Bridge Research & Engineering: Collaborate with cross-functional teams to identify research gaps and translate them into production-ready features.
Own the Lifecycle: Lead the end-to-end process-from reading the latest ArXiv papers to A/B testing and monitoring model performance in a live environment.
Experiment Freely: Dedicate time to "deep-work" sessions, testing unconventional hypotheses and new algorithmic approaches.
Requirements: The Foundation: An advanced degree (MSc/PhD) in a quantitative field or equivalent "in-the-trenches" industry experience.
The Toolkit: at least 5 years of experience in applied research, specifically deploying ML algorithms into high-throughput online environments.
The Hybrid Edge: Strong software engineering fundamentals; you dont just design models, you understand how they fit into the code stack.
Critical Thinking: The ability to dismantle a scientific paper, critique its methodology, and implement its core findings effectively.
Communication: A knack for making the complex simple. You can explain a transformer-based ranking system to a peer or a product manager with equal clarity.
Please submit your CV in English.
This position is open to all candidates.