About the job
ABOUT US:
Join our innovative team at Sportradar, a global leader in sports technology. We are searching for a Senior Software Engineer to contribute to our cutting-edge Argos platform—our cloud-native, low-latency infrastructure dedicated to computer vision processing. In this pivotal role within Sportradar's AI unit, you will collaborate with a talented group of data scientists, developers, and DevOps engineers to create advanced infrastructure solutions tailored for computer vision, machine learning, and data analytics.
Computer vision is increasingly integral to how we collect and leverage sports data across our diverse product offerings, which serve sports media, betting, and coaching sectors. By joining Sportradar, you will help us entertain millions of sports fans worldwide.
THE CHALLENGE:
- Research, design, develop, deploy, and manage daily operations for real-time, low-latency computer vision processing solutions on AWS cloud.
- Collaborate with computer vision researchers to integrate and productize innovative CV models.
- Advance our technology stack and architectures that drive computer vision and AI workloads, working alongside a dynamic team of skilled developers and data scientists.
- Mentor fellow engineers and oversee code/design reviews.
- Enhance system reliability and performance.
ABOUT YOU:
- Proficient in programming with a focus on strong Python expertise and hands-on experience in developing production-grade solutions.
- Extensive experience with containers and orchestration frameworks such as Docker and Kubernetes.
- Solid understanding of system observability and reliability.
- Familiarity with modern software development practices including Agile methodologies, Git, CI/CD, and code review processes.
- Comfortable using AI coding tools and advanced technological solutions.
- Bonus: Experience in Golang and/or Java development.
- Bonus: Familiarity with Kubernetes Operators.
- Bonus: Proven experience in productizing CV/ML models.
- Bonus: Knowledge of machine learning/deep learning concepts with hands-on experience using frameworks like PyTorch, Keras, TensorFlow, or MXNet.
- Bonus: DevOps experience, including design, setup, and administration of cloud infrastructures.

