ml engineer for live sports

Описания нет

• Lead end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science for automated sports metadata generation and key-event detection in live content and data streams
• Generate actionable insights into player performance, contextual statistics, and injury risk by designing models with responsible and ethical AI principles embedded from design through deployment
• Integrate model-driven insights into personalization engines and tailor recommendations based on favorite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate data use
• Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own productionization from data ingestion through deployment and ongoing model monitoring
• Design, architect, and operate low-latency, highly reliable cloud-based AI systems for live sports, ensuring resilient performance during peak traffic, responsible real-time model behavior, and an optimal balance between cost, latency, and production-scale performance

• Extensive lead-level engineering experience delivering data-driven ML systems, with ownership of technical direction, mentoring, and delivery
• Working knowledge of modern ML techniques, including Generative AI, and using emerging models to extract insights from multimodal sports data such as numerical, spatial, video, or metadata
• Advanced Python expertise and hands-on experience with ML/DL frameworks such as PyTorch and TensorFlow, including taking models from experimentation into production model serving
• End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code
• Technical leadership experience mentoring and guiding Senior and Mid-Level Data Scientists in their day-to-day work and career development
• Experience in a fast-changing environment, adaptability, and the ability to support the team through uncertainty and pivots

• Competitive salary
• Access to advanced technologies and tools for AI development
• Professional growth and development opportunities in a dynamic tech environment
• Collaborative work environment focused on innovation and advancing sports technology