Staff Machine Learning Engineer

Argentina - Remote First

We're looking for a talented and passionate Staff Machine Learning Engineer, to join Wildlife's Creatives Tech team in Brazil, Argentina, or Uruguay. We are a remote-first company.

Wildlife is one of the largest gaming companies in the world. Besides building amazing games, part of the reason it has been super successful has been its ability to acquire new users more efficiently than other companies. To keep strengthening its competitive advantages, we have an in-house team of artist / video producers / engineers making video game ads (we produce around 400 creatives per month).

Creatives Tech's main goal is to enable Creatives operation, by testing all the ads, selecting the ones that have the biggest potential, rolling them out into our 1200 campaigns across multiple platforms (Facebook, Google, etc), and feedback the loop with data helping the ads creation get better. 

We know that the work we do has a high impact on our company's success and culture. The right person for this position is curious by nature, and comfortable in a “take the initiative” environment, loves solving problems, and can thrive in a fast and growing business. 

What you'll do

  • Lead Creatives technology landscape across multiple disciplines: Backend Engineering, Data Engineering, Machine Learning Engineering, and Data Science;
  • Ensure high-quality design reviews which meet business and architectural goals and drive critical feedback on design issues;
  • Participate in strategic planning to achieve technical and business goals;
  • Work closely with team members and also people from other departments in order to lift their technical knowledge and performance as well as improve our products;
  • Be responsible for the overall performance and quality being delivered by our team in order to design and lead the execution of improvements;

What you'll need

  • University degree in courses related to computing such as Computer Engineering, Computer Science, Information Systems, and Systems Analysis and Development;
  • Experience with model deployment at scale;
  • 3+ year of experience with cloud environments (AWS, Google);
  • 3+ years of experience working as machine learning engineer on technically challenging problems;
  • Knowledge of machine learning algorithms that is both deep and broad;
  • Experience in software engineering is a plus;
  • Knowledge and experience with Python, Go, Spark and Databricks are a differential;
  • Knowledge and experience with Airflow or other workflow management tool are also a differential.

More about you

  • You are an autonomous independent thinker;
  • You are a resourceful person with a go-getter attitude;
  • You are passionate about the data industry and thirsty for innovation;
  • You are not afraid to propose and explore new initiatives;
  • You are a determined and persistent leader who wants to deliver results;
  • You are flexible, bold, and excited to help build something awesome and share it with the world;
  • You understand the impact of a highly-satisfied, excited team;
  • You are passionate about working on and solving problems;
  • You are a team player. You're willing to help out wherever needed.

About Wildlife

Wildlife is one of the leading mobile game developers and publishers in the world. We have released more than 60 titles, reaching billions of people around the globe. Today, we have offices in Brazil, Argentina, Ireland, and the United States. Here, we create games that will excite, intrigue, and engage our players for years to come!

Equal Opportunity

Wildlife is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, colour, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law. We're committed to providing accommodations for candidates with disabilities in our recruiting process.

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