Company Description

We’re the world’s leading sports technology company, at the intersection between sports, media, and betting. More than 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries rely on our know-how and technology to boost their business.

Job Description

Interested in Artificial Intelligence, Computer Vision, Deep Learning and other modern technologies? Then the Automated Content team within Sportradar is the right fit for you. We are enhancing the sports experience for fans, athletes, and teams across the globe through world-class AI solutions and are committed to advancing the state of the art of Sport through continuous innovation with a specialized and distributed team focused on research and development in areas such as computer vision, machine learning, deep learning, data science and beyond. We are on a mission to automate sports content creation - the data and video – that feeds products and services we deliver to our partners. The possibilities to revolutionize the world of sport are vast, and we are only at the beginning of our journey.

Our cutting-edge technologies will revolutionize the way individuals interact with and participate in sports. Our objective is to create innovative hardware and software solutions leading to automated viewing experiences, real-time statistics, and event forecasting. By doing so, we are enhancing the lives of coaches, athletes, and fans by developing products that cater to their evolving needs and requirements, as well as enabling an experience where people can engage with sport in new and meaningful ways.

We seek a talented ML Ops Engineer to join the Systems Squad: a diverse, highly skilled, and enthusiastic squad part of the broader Automated Content Tribe.

About the role

As ML Ops Engineer, you will play a key role in setting up and maintaining infrastructure for software solutions that empower the Computer Vision Squads (also part of the Automated Content Tribe) to more easily and reliably train, evaluate, deploy, and monitor complex computer vision and AI systems in production. You will use your ML Ops expertise to propose and implement software solutions, based on requirements, that will help the team deliver quickly and efficiently.

Responsibilities

• Design, build and improve the software delivery lifecycle for a broad array of products and services
• Desire to automate all things, coach and guide your peer development community and a passion for reproducible results
• Enable teams to work efficiently and effectively through technology and ways of working solutions
• Research new technologies and methodologies to address technical issues
• Contribute to the continuous improvement of existing software solutions

The challenge

• Design, build, test, deploy and maintain cloud infrastructure for our ML/DL solutions
• Improve the reliability and efficiency of CI/CD pipelines
• Help reducing the time to market of our computer vision solutions
• Craft reusable frameworks that simplify delivery and observability of our computer vision solutions
• Write clean, scalable, documented, and understandable code
• Participate in code review processes, when area of expertise is applicable
• Build reusable code libraries, when those are required

Your skills

• Proficiency in scripting languages such as python, bash, golang. Experience with other languages will be considered a plus
• Proven experience in CI/CD pipelines for software release lifecycle
• In depth Cloud experience with AWS
• Highly proficient with IaC and Configuration Management tooling (Terraform)
• Demonstrated experience with productization of ML/DL solutions
• Experience with frameworks for web APIs (Flask, FastAPI, ..) and API specifications (OpenAPI, gRPC)
• Solid knowledge of containerization technologies and processes
• Experience with databases (relational and non-relational)
• Experience with Grafana and Prometheus
• Experience with k8s
• Excellent communication skills
• Ability to work independently and as part of a team
• Strong organizational and problem-solving skills

Additional Information

Sportradar is an Equal Opportunity Employer. We are committed to encourage diversity within our teams. All qualified applicants will receive consideration without regard to among other things, your background, status, or personal preferences