AppThis is an international mobile ad tech company focused on the global app ecosystem. Founded in early 2014 by two experienced tech entrepreneurs, AppThis has already delivered over 10 million app installs for global app developers. Our approach is technology and data first with an eye to deliver globally. We are seeking a Machine Learning Engineer to play a key role supporting the growth of the business by developing critical components of our data platform and advertising products. Relocation assistance to our Denver Headquarters is available.

You will be joining a fun team of experienced engineers and analysts who have strong technical backgrounds and successful track records using cutting edge technology and data science for mobile advertising. The company culture is dynamic and fast-paced, empowering people to get shit done with no drama or politics. The engineering culture echoes that mentality with rapid, iterative release cycles and clear insight into how your work impacts revenue.

This position is heavily focused on developing and expanding the data platform to propel revenue growth. We are currently serving billions of impressions annually and expect that to grow by multiple orders of magnitude.

As a Machine Learning Engineer, your responsibilities will include:

• Architect machine learning systems capable of handling > 10K events per second

• Hypothesize, test, and evaluate new targeting algorithms

• Expand infrastructure and online experiment capabilities

• Apply optimizations to improve core algorithms

• Develop processes for audience segmentation

​Job Qualifications

• Proficient in object oriented programming

• Strong analytical and problem solving skills

• Experience doing analysis in SQL and R, Python, Matlab, or similar

• Skilled in data storage/manipulation/processing, especially at scale

• Massive attention to detail

Pluses

• Experience in Internet Advertising industry

• Proficient in Java or Scala

• Background in mathematics/statistics

• Experience with design of online experiments

• Understanding of major recommendation and classification algorithms

• Experience with distributed computing; and popular “Big Data” tools