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Machine Learning Engineer at Wildlife Studios

About the Team

At Wildlife we keep an international standard in terms of technology, development and quality of service, as our primary source of innovation and operation is data itself. We deal with an ever-growing quantity and variety of data from our games and we collaborate with our Data Science and Data Engineering teams based on several locations worldwide.

This is a unique opportunity to join a fast-growing company with increasing needs for Machine Learning and AI workloads, a huge Dataset, and an ecosystem (Feature Store and AI microservices framework) in the decisive stages of architecture and development.

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 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.

This role is key for building 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.

What you'll do:

    Work 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 their 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:

    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.

  Experience with Spark and data transformation.

English skills are required (Conversation & reading skills).


    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.

    Experience serving, deploying and monitoring Kubernetes based ML/AI workloads (Kubeflow, Knative for ML, and GCP).

    Studies 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 build the best technology company!

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