AI Engineer

Wearehaystack — United Kingdom · Posted ~3 hours ago

Senior

Skills

Computer vision Machine learning Generative AI Data science MLOps A/B testing Model deployment Model monitoring Computer Vision Machine Learning Data Science A/B Testing

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Summary ✨ AI‑Generated

Lead the end-to-end development and productionization of AI solutions combining computer vision, machine learning, generative AI, and data science. Design models and experiments, build MLOps capabilities, integrate insights into personalization systems, and continuously monitor production performance while prioritizing fairness, transparency, and responsible AI.

Highlights

End-to-end AI engineering role spanning computer vision, machine learning, generative AI, experimentation, MLOps, and production deployment. Strong opportunity to build impactful models while applying responsible and ethical AI principles.

Description

We're hiring on behalf of a Haystack partner! The Role • Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. • Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. • Integrate model-driven insights into personalization engines, tailoring 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. What You'll Need • 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 how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata). • Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch, 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 including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. • Experience of working in a fast-changing environment demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary. What's On Offer • Competitive salary • 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 and pushing boundaries in sports technology. Apply via Haystack today!