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Sportradar is seeking a Backend Software Engineer to join its AI unit and help develop Argos, a cloud-native, low-latency infrastructure platform for computer vision processing. You will work alongside experienced data scientists, developers, and DevOps engineers to build innovative infrastructure solutions for computer vision, machine learning, and data analytics workloads.
Key responsibilities include:
- Research, design, develop, deploy, and maintain solutions for real-time, low-latency computer vision processing hosted on AWS.
- Collaborate with computer vision researchers to integrate and productionize computer vision models.
- Contribute to the evolution of the technology stack and technical architectures supporting computer vision and AI workloads.
Sportradar is a global sports technology company serving over 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries. The company operates an office-first model with team members working on-site five days per week, though certain exemptions may apply by location.
The role offers a collaborative international environment with colleagues across Europe, Asia, and the US; flexible working hours within the office-first structure; professional development planning; an inclusive community with employee resource groups; global employee assistance; wellness apps (Calm, Reulay); online training; and team-building activities.
REQUIREMENTS:
- Demonstrable hands-on experience developing production-grade solutions in Python.
- Hands-on experience with containers and container orchestration (Docker, Kubernetes).
- Comfort with modern software development methodologies: agile, git, CI/CD, code review.
- Comfort using AI coding tools and agentic technologies.
- Bachelor of Science in Computer Science, Engineering, Mathematics, Statistics, or related field (equivalent experience acceptable).
- Fluent in English (written and spoken).
- Autonomous, rigorous, creative, and collaborative.
BONUS QUALIFICATIONS:
- Experience with Golang and/or Java development.
- Demonstrated experience productionizing CV/ML models.
- Understanding of machine learning/deep learning concepts and hands-on experience with frameworks (PyTorch, Keras, TensorFlow, MXNet).
- DevOps experience: infrastructure design, setup, and administration; cloud services (AWS/Azure).
