About the Team

Data is a team sport. We are professionals and team players with a massive impact on the company's data-driven culture so as we release tools, we also coach users and developers to adhere to best practices and unfold their potential. Is essential for us to support each other inside the team and be aware of each other's needs for knowledge to promote a learning culture through cooperation and incremental development. Everyone here must come with some experience, knowledge and good spirit to learn and support the team in its effort to evolve Data projects.

About the Role

Machine Learning workloads are growing consistently in importance and complexity at Wildlife, and the Data teams (Data Platform and Machine Learning Engineering) are taking a leading role on projects that involves the challenging work of developing, deploying, serving and monitoring of ML services across the Globe. We have chosen Kubernetes and its ecosystem (Kubeflow, Knative, Tensorflow Serving, Pachyderm, Argo) to help us in this endeavour and to do so we need more Kubernetes experts interested and focused on ML/AI workloads at the Data Platform team. These professionals will be involved in the first POCs of some Kubernetes based AI infrastructures, ML services and its architecture definitions. They will assist with the growth of the AI/ML toolset at the company working side by side with MLE team in some of the most critical projects inside the company like Kubeflow customization and service mesh for machine learning services.

More about you

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 to deliver great results.

What you'll do

Working proactively and closely with other data platform engineers to developing and defining the architecture of our cloud-based data infrastructure, creating SLOs, improving monitoring and deployment process to serve our most data-intensive services;

Work proactively with other cloud infrastructure teams to improve cloud practices and propose new solutions on Machine Learning and Artificial Intelligence infrastructure;

Contribute to design, coding, testing and debugging steps of the development cycle of Data tools and services to ensure low operational footprint, reliability, availability, and reproducibility of our cloud infrastructure;

Create, customize and test charts on Kubernetes to our ML/AI toolsets adapting existing ones and/or developing new ones to provide serving, testing and observability capabilities to all AI services.

Build APIs, IaC and automation to automate and serve data-centred stateful infrastructure hosted on Kubernetes clusters as all final releases of our Data Infrastructure Services are backed on Kubernetes (100%).

What you'll need

At least 2 years of experience as a Data, Software or Infrastructure engineer (data related or not) on Kubernetes.

BS in Computer Science, Engineer (Software or others), Statistics, Physics or a related field (we also consider candidates without a degree but with outstanding experience);

Kubernetes Administration Certification (CKA);

Practical experience with Service Mesh (developing or managing);

Experience with scripting languages such as Shell, Lua, Python;

Developer experience using Docker and Kubernetes;

Experience with cloud services (AWS or GCP);

Experience creating CI/CD processes.

Plus

Experience with orchestration frameworks like Apache Airflow;

Experience managing the infrastructure of open-source NoSQL Databases (Cassandra, MongoDB, Redis, etc);

Experience with cloud best practices on AWS (tagging, IAM for example);

Practical knowledge on Network specification and operation, especially on AWS;

Proven experience applying SRE practices (especially observability and automation);

Experience using Terraform for IaC;

Proven experience serving, deploying and monitoring Kubernetes based ML/AI workloads (Kubeflow, Knative for ML, Tensorflow).

We welcome people from all backgrounds who seek the opportunity to help build the best gaming company, where everyone thrives.