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описание
Haystack’s partner develops sports technology solutions using AI to generate automated sports metadata, detect key events in live content and data streams, and provide insights for player performance, contextual statistics, and injury risk.
задачи
Lead the 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 for player performance, contextual statistics, and injury risk by designing models with responsible and ethical AI principles 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 use of data;
Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end 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 scenarios, ensuring resilient performance during peak traffic, responsible model behavior in real time, and an optimal balance between cost, latency, and production-scale performance.
требования
Proven extensive lead-level engineering experience delivering data-driven ML systems with clear ownership of technical direction, mentoring, and delivery;
Working knowledge of modern ML techniques, including Generative AI, and extracting insights from multimodal sports data such as numerical, spatial, video, and metadata;
Advanced Python expertise with hands-on use of 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 practices;
Proven technical leadership experience mentoring and guiding Senior and Mid-Level Data Scientists in their day-to-day work and career development;
Experience working in a fast-changing environment, demonstrating adaptability and the ability to support the team through uncertainty and pivot as necessary.
условия
Access to advanced technologies and tools for AI development;
Opportunities for professional growth and development in a dynamic tech environment;
A collaborative work environment focused on innovation in sports technology.
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