ScaleMonk

26 - 50 Employees
11 - 25 Engineers
Private Funding
Series A

ScaleMonk helps mobile-first companies scale distribution while maintaining a target return. By collecting post-install data from its clients, ScaleMonk is able to optimize in real-time the ad spend that goes to different campaigns across hundreds of mobile advertising channels.

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Active Roles
Why join us?
  • ScaleMonk is backed by Bessemer Venture Partners

  • ScaleMonk is tackling a 64B USD market

  • Doug Loyer, one of ScaleMonk’s co-founders, previously co-founded Fractional Media, a performance DSP that was acquired by Machine Zone. Fractional achieved over $110M/year in profitable programmatic media buys for app install performance campaigns

  • We are tackling extremely hard technical problems from scratch

  • You will gain more experience here than you would as a cog in a giant company. You will be exposed to more scale, newer technology and learn more

  • We do a lot of fun stuff! Some off-site team events we organized recently were: (i) going to a Warriors vs Lakers NBA game in a VIP area with open food and open bar; (ii) going wine tasting in Napa Valley for the whole day!


Engineering at ScaleMonk
Engineering team and processes

We have a small, tightly focused engineering team executing on a Kanban system. We do daily standups often followed by design jams with people focused on a common part of the project. Source code control is via git.

Technical Challenges

We handle 1,000,000 ad requests per second and track 1.8 billion device profiles. We train ML models to directly control millions of dollars of ad spend.

Projects you might work on
  • Build a vectorized targeting system that is able to match an inbound request against thousands of campaigns across many different targetable criteria. A good implementation reduces the number of campaigns that need to be considered and uses bit arrays to vectorize the matching process.

  • User clustering. Using trillions of user observation for billions of users, find user clusters using matrix factorization and clustering the resulting user embeddings.

  • Ad value prediction. Use ML models to predict the value of an ad impression. Take into account everything we can observe about the user and the ad impression. Must be trained 3x per day over 1B training examples.

Tech stack
Go
Python
Hadoop
Apache Spark
Tensorflow
Keras
JavaScript
TypeScript
CSS
HTML

Working at ScaleMonk

Teamwork: We work together as a team and the team succeeds together. Building anything of meaningful scale is a team sport. We only succeed if we have the same goal and work together to reach that goal

Reward and Recognition: The members of the team have an impact. Your accomplishments will be noticed and appreciated.

Customer Focus: We succeed by providing value to our customers. Results matter. We execute better and provide better value than our competitors.

Simplicity and Elegance: Good solutions are no more complicated than they need to be. At Scalemonk, we find the right tool for the job and are always looking for a better solution

Generous Vacation

Unlimited vacation policy

Gym/Fitness

Our office provides complimentary access to a gym

Flexible Hours

We care about productivity

Health Insurance

We provide full medical, dental and vision coverage. We pay 100% of its monthly cost for you and your dependents

Relocation

We will help you move

Maternal/Paternal Leave
Free Food
Work from Home
Team Activities
Transportation
Workshops/Conferences
Travel

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