Offer summary

Qualifications:

Proven experience as an MLOps Engineer or similar role in machine learning operations., Strong knowledge of cloud services, containerization (Docker, Kubernetes), and CI/CD pipelines., Familiarity with ML tools like MLflow for experiment tracking and model governance., Experience with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation..

Key responsibilities:

Design and implement infrastructure for ML model training, testing, deployment, and monitoring.

Collaborate with ML engineers and data scientists to enhance model operationalization and CI/CD integration.

Manage and monitor containerized environments and model serving infrastructure.

Automate workflows and contribute to reproducible infrastructure deployments.

Better Collective is a digital sports media group operating a strong portfolio of national and global sports media brands. We are on a mission to excite sports fans through engaging content and foster passionate communities worldwide. Incorporated in Denmark in 2004, Better Collective remains under the direct management of its founders, Jesper and Christian. Since our inception, we have undergone substantial growth, driven by successful acquisitions to realize our vision of becoming the leading digital sports media group. Headquartered in Copenhagen, Denmark, and listed on Nasdaq in Stockholm, Better Collective operates globally with more than 20 offices around the world. At its core, Better Collective covers a vast range of sports that spans from the most popular leagues such as the Premier League and NFL to niche competitions. With our media brands, fans can explore the exciting world of sports through various content formats such as exclusive videos, engaging podcasts, editorial sports news as well as expert insights and tips into the latest and upcoming sports events. Our wide range of content engages an audience of more than 180 million loyal fans each month across our portfolio of national and international sports media brands. These brands include Action Network, HLTV, Playmaker HQ, VegasInsider and FUTBIN - just to name a few. We have a dream team of highly talented employees with a unique set of digital capabilities and a strong track record in attracting and driving sports fans to our sports media. In combination with engaging content offerings, we are able to build and grow a strong and loyal audience across our brands.

Job description

You are:

An experienced MLOps Engineer who thrives on building the backbone of production-grade ML systems. You enjoy bridging the gap between model development and production, creating scalable infrastructure, and empowering ML teams to ship models with confidence. You’re comfortable working across cloud services, containerized environments, and CI/CD pipelines—and you understand the importance of reproducibility, monitoring, and automation.

You will:

Design and implement infrastructure for ML model training, testing, deployment, and monitoring.
Collaborate with ML engineers and data scientists to streamline model operationalization and CI/CD integration.
Manage containerized environments (Docker, Kubernetes/ECS) and model serving infrastructure.
Monitor production ML systems for performance degradation, data drift, and retraining needs.
Use tools like MLflow to track experiments, manage model versions, and support model governance.
Automate workflows using tools like Airflow, Step Functions, or similar orchestration platforms.
Contribute to IaC (e.g., Terraform or CloudFormation) to ensure reproducible infrastructure deployments.