Wildlife is one of the leading mobile game developers and publishers in the world. In eight years, our gaming titles have been downloaded over 1.5 billion times providing fun to millions of people, every day, everywhere.We are not done yet. We aspire to develop games that will be remembered by generations.
To achieve this goal, we pursuit to be best-in-class in each of our major disciplines: Product, Engineering, Art, Marketing, and Data. That’s why we are rapidly expanding and building talented and passionate teams in our offices in Argentina, Brazil, Ireland, and US.
About the Team
Here at Wildlife, especially at the Machine Learning Engineering team, we keep an international standard compatible with silicon valley companies in terms of technology, development and quality of service and Data-driven companies as the primary source of innovation and operation is data itself. Here we have real technical challenges as we deal with an ever-growing quantity and variety of data from our games. We are collaborating with Data Scientists and Data Engineers based on several locations worldwide with the same high professional standards and interested around ML challenges. We do have a place and structure to create the next generation of ML tools, practices and products.
About the Role
Machine Learning workloads are growing consistently in importance at Wildlife. In this direction, the Machine Learning Engineering team is taking a leading role on projects that involve the challenging work of developing, deploying, serving and monitoring of AI services across the Globe and the continuous job of setting up a high-quality software development standard for ML projects. The new members of the Team will sum efforts with the existing MLE members to build our reference AI framework dedicated to managing all ML development pipeline: from development and iterating to deployment, versioning, testing and monitoring. From helping to structure our feature store to architect our AI microservices framework. This is a unique opportunity to join a fast-growing company with increasing needs for Machine Learning and AI workloads, huge Dataset and an ecosystem (Feature Store and AI microservices framework) in the decisive stages of architecture and development.
Who you are
● 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;
● Demonstrate critical thinking and problem-solving capabilities both independently and collaboratively;
● 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.
What you'll do
● Working proactively and closely with Data Scientists and Data Engineering teams on the various group projects developing tools for data exploration and feature engineering pipelines;
● Design, develop and test tools and frameworks to improve Data Science teams productivity speeding up the development cycle.
● Build AI microservices and its framework on our Kubernetes clusters and Cloud services in order to provide consistently high-performance and scalability of our AI services and models;
● Set and promote high software engineering standards for our Machine Learning projects.
What you'll need
● BS in Computer Science, Engineer (Software or others), Statistics, Physics, Economics or a related field;
● At least 2 years of professional experience that can be composed of at least 1 year as a Machine Learning Engineer and the other year as a Data Scientist, Data Engineer or Software Engineer;
● Experience with C++, Python, Scala, Java, R, Shell or Go (at least 2).
● Real-world experience with software development and Statistical or Data modelling.
● Initial experience with training, deploying and serving production Machine Learning models and services.
● Proven experience with Spark and data transformation;
● Experience with orchestration frameworks like Apache Airflow;
● Know how to design and code REST APIs and Microservices;
● Experience with TensorFlow or Pytorch (training and serving);
● Experience with real time data development skills;
● Developer Experience using Docker and Kubernetes;
● Proven experience serving, deploying and monitoring Kubernetes based ML/AI workloads (Kubeflow, Knative for ML, and GCP);
● MSc or PhD in Computer Science, Statistics, Physics, Economics or a field related to computer vision and deep learning. In all cases, relevant work with the use of machine learning is required.
We welcome people from all backgrounds who seek the opportunity to help build the best gaming company, where everyone thrives!