Research Scientist

We are  a group of research scientists and engineers building cutting edge technology at the intersection of machine learning and adtech.

The core of our work is focused on:

• Building ads delivery systems that deliver the most relevant products to users and drive business results.

• Processing and handling tens of billions of rows of data per day, and processing one million requests per second.

• Integrating tabular, text, image, and video data into a cohesive system to improve ads delivery.

• Running large-scale A/B tests to measure results.

Why Applovin?

Our team has a consistent track record of driving business impact through technology — building one of the world’s highest-performing ads recommendation systems and fueling Applovin’s ~25x business growth over the last 2+ years. At Applovin, the feedback loop for Research Scientists is exceptionally fast. You can develop a new model, launch an A/B test, and ship it — all within days or weeks. What might take months or even years elsewhere happens here at the pace of your execution. 

Even as we’ve scaled, our pace hasn’t slowed — we continue to ship meaningful improvements that move the needle, and there’s still enormous opportunity for the right candidate to make an immediate impact and further our business growth. Despite the size of our business, we operate with a remarkably efficient engineering team — fewer than 100 engineers power everything we build, which means every individual has outsized responsibility, autonomy, and influence.

If that kind of fast-paced, high-impact environment excites you, we’re looking for teammates eager to solve hard problems and drive meaningful business results from day one.

About you:

A good candidate generally has:

• Experience working with state of the art Machine Learning/Deep Learning models to solve hard problems.

• Strong programming skills in Python and experience with Deep Learning frameworks (preferably PyTorch).

• Strong mathematical skills, and the ability to understand and interpret data.

• The drive to want to make an impact on the company you work for.

It’s a bonus if you have:

• Experience working with large datasets and distributed computing frameworks.

• Strong C++ or Java programming ability in addition to Python.

• Prior experience working with recommendation models specifically.