Machine Learning Engineer

Team Engineering in Sao Paulo, BRA

We're looking for a talented and passionate Machine Learning Engineer to join Wildlife's team in São Paulo, Brazil. 

As a MLE at Wildlife you will be part of the team developing the most advanced ML solutions in the mobile gaming industry. Our ML solutions set Wildlife apart from competitors by optimizing our revenue streams and allowing for a personalized gaming experience. Develop state-of-the-art end-to-end ML solutions for user acquisition, ad optimization, dynamic pricing, personalization and more. Sum efforts with our ML Platform team to design and build an AI microservices framework to scale our MLOps. Be ready to create business critical ML solutions with a global audience of millions of users producing over Billions of events and terabytes of data every day.

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

  • Collaborate with a multi-functional agile team spanning Product Managers, Data Scientists, Data Engineers and Developers to conceive and build machine learning based products and services.
  • Partner with Data Scientists to develop prototypes for proof-of-concept validation.
  • Turn prototypes and concepts into working, production-rate, machine learning solutions at scale.
  • Help drive optimization, testing and tooling to improve quality and response of our machine learning solutions.
  • Set and promote high software engineering standards across our Machine Learning projects.
  • Work in a globally competitive company. 

What you'll need

  • A degree in a quantitative discipline such as Computer Science, Engineering, Mathematics, Statistics. A plus if you hold a MSc or Ph.D. in STEM.
  • Great Software Engineering skills with at least 2 years of experience, of which at least 1 year experience as a Machine Learning Engineer, Data Scientist or Data Engineer.
  • You have a sound understanding of Machine Learning fundamentals, data structures and algorithms. 
  • Real-world experience with Statistical or Data modelling and initial experience training, deploying and serving ML models and services.
  • A solid understanding of Python, Shell and experience with Spark are a must. A plus if you are comfortable with Go or Scala.
  • Proven experience with Big Data toolset and ML pipelining tools. Our pipelines are based on Spark and Airflow. A plus if you have experience with Kubernetes based workloads using kubeflow, mlflow or sagemaker.
  • Experience with CI/CD/CT/CM and pipeline automation are a plus. We use Airflow but experience with Kubernetes based workloads using kubeflow, mlflow or sagemaker.

More about you

  • You are excited to work in a high-performant and innovative team that values a strong DevOps culture.
  • You are capable of tackling loosely defined problems and working both independently and collaboratively.
  • Enjoy working with complex business logic and deal with large scale to build low latency systems;
  • Smart and creative, both, you have the ability and persistence to solve problems, big and small. Curious by nature, you're constantly looking for ways to improve upon things;
  • You're flexible, fearless, and excited to help build something;
  • You're hands-on, in the right ways; willing and able to do what's needed, no matter the task.
  • You can communicate with an international team in English and have working proficiency in Portuguese.

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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