Who we are
RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad-buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel.
Founded in 2012, and now operating in 90+ markets, RTB House has always been private-by-design. It embraces first-party advertising and a relentless approach to innovation. RTB House AdTech highly optimized bidding engine handles 400 million model inferences every second.
About the role
As a Staff Research Team Lead you will lead a small team (4–8) of ML researchers while staying deeply hands-on. ML is at the very center of RTB House, and you will have a strong, immediate impact on our core metrics. This is a hands-on leadership role: we expect you to perform technically at the level of a Staff ML Researcher, while also owning your team's direction, growth, and delivery.
We are looking for a strong individual contributor who will lead research projects of high scope and ambiguity. The following skills will be crucial:
- Ability to solve unclear problems. You will have to understand the core of the issue, define the goal and how to measure success, and find the most effective way to solve the problem.
- Hands-on ML expertise. This is an applied research role: we build ML systems that run in production. You will write code, train models, run experiments, and ship — the measure of success is real-world impact.
- Being results oriented. We value a healthy drive to solve problems effectively, by starting simple and using complex tools only when necessary, always striving for a simple, elegant solution.
- Team leadership. You will manage 4–8 researchers: setting direction, prioritizing projects, unblocking, and growing people through feedback and mentorship.
- Vision and execution. Identify high-potential projects, create a vision, communicate with stakeholders, and above all, execute — through your team, not only yourself.
- End to end ownership. You will own the projects from conception, through analysis, research, building a proof of concept, testing, to final implementation and deployment.
- Effective communication. In this role you will collaborate with many people, and it's crucial to communicate well and organize the work effectively.
You Will:
- Manage a team of 4–8 researchers: set priorities, review work, and support their career growth.
- Balance your own hands-on research with team leadership, aiming at a 50/50 split.
- Identify, define, and drive research projects with company-wide scope and direct impact on our core metrics.
- Design and implement models, most often deep neural networks, used to predict the behavior and preferences of Internet users.
- Develop and test new approaches to modeling key issues, such as bidding in first-price auctions.
- Conduct and analyze A/B tests of new solutions.
- Follow and analyze the latest works in the field of Machine Learning, and translate them into practical improvements.
- Mentor researchers and shape research practices across teams.
Selected technologies used:
- Python, Java, Scala
- PyTorch, NumPy, Pandas
- TPU, JAX
- Jupyter Notebooks
- BigQuery, GCP
Expected experience
- 5+ years of experience as researcher or engineer.
- 2+ years of hands-on experience with Machine Learning / Data Science.
- Proven leadership experience, with at least 2 years of managing and mentoring an engineering or research team.
- Proficiency in programming.
- Sound mathematical knowledge and intuitions.
Nice to have
- Strong theoretical mathematics framework: statistics, probability, discrete mathematics, combinatorics.
- Experience in AdTech is a plus, but not required.
- Experience hiring and building research teams.
- Experience leading applied research in a production environment.
What we offer
- Technology: access to the latest technologies and real opportunity to use them in large-scale and highly dynamic projects; working on extensive and rich datasets.
- Impact: your work will be immediately impacting the company's business results and outcomes globally as well as shaping the growth and direction of your own team
- Wellbeing: remote and on-site work possible. Flexible cooperation hours.
- Culture: a team of enthusiasts with wide experience in ML who willingly share their knowledge and learnings on a daily basis, no BS environment.
- Purpose-Driven Work: being at heart of the system, your growing knowledge and competences will be used in practical applications directly connected to business results.
