Can AI help win football matches? Arsenal is hiring an engineer to plan wins. Here's how to apply
The vacancy is another sign of AI's expanding role in elite sport. Modern football clubs collect enormous volumes of data from tracking systems, video feeds, player movement, event logs and performance metrics.
- Jul 24, 2026,
- Updated Jul 24, 2026 10:23 PM IST
Arsenal's next signing won't wear a jersey or score goals. Instead, the Premier League club is looking for a research engineer who can help build cutting-edge artificial intelligence systems designed to improve coaching, match analysis and on-pitch decision-making.
The opportunity came into the spotlight after a research engineer at Arsenal FC, announced the opening on X (formally twitter). "We're hiring a Research Engineer at @Arsenal to work directly with our Men's First Team! We're building state-of-the-art AI models for the football domain. This role will focus on building the application layer for our research to advance coaching and analysis workflows."
The opening reflects how elite football clubs are increasingly treating artificial intelligence as a competitive advantage, investing in technologies that can convert massive volumes of match data into actionable insights for coaches and analysts.
According to Arsenal's job listing, the successful candidate will join the club's Data Analytics team and work closely with the Men's First Team Analysis department. The role involves planning, building and deploying internal products that support football analysis while translating advanced AI research into tools that coaching staff can use in their day-to-day work.
Rather than conducting research in isolation, the engineer will collaborate directly with analysts and coaches to develop data-driven applications, automate analysis workflows and identify opportunities where AI can improve existing football processes. The club says the position is intended to accelerate the adoption of proprietary technology across coaching and performance analysis.
What Arsenal is looking for
The role requires a strong quantitative background in disciplines such as computer science, data science, mathematics or statistics, alongside expertise in software engineering and machine learning.
Candidates are expected to be proficient in Python, SQL and JavaScript or TypeScript, while also having experience with deep learning frameworks such as PyTorch, JAX or TensorFlow. Familiarity with modern data science libraries and an understanding of football are also listed as important qualifications.
The successful applicant will also be expected to design scalable full-stack applications, build interfaces that present complex football insights clearly, and work in the fast-paced environment of a professional football club, including collaborating around training and matchday schedules.
AI's growing influence on football
The vacancy is another sign of AI's expanding role in elite sport. Modern football clubs collect enormous volumes of data from tracking systems, video feeds, player movement, event logs and performance metrics. Machine learning models are increasingly being used to analyse tactical patterns, evaluate player performance, optimise training loads and support in-game decision-making.
Academic research has also highlighted football as one of the fastest-growing real-world applications for artificial intelligence, with advances in computer vision, deep learning and spatiotemporal modelling enabling increasingly sophisticated analysis of players and teams.
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Arsenal's next signing won't wear a jersey or score goals. Instead, the Premier League club is looking for a research engineer who can help build cutting-edge artificial intelligence systems designed to improve coaching, match analysis and on-pitch decision-making.
The opportunity came into the spotlight after a research engineer at Arsenal FC, announced the opening on X (formally twitter). "We're hiring a Research Engineer at @Arsenal to work directly with our Men's First Team! We're building state-of-the-art AI models for the football domain. This role will focus on building the application layer for our research to advance coaching and analysis workflows."
The opening reflects how elite football clubs are increasingly treating artificial intelligence as a competitive advantage, investing in technologies that can convert massive volumes of match data into actionable insights for coaches and analysts.
According to Arsenal's job listing, the successful candidate will join the club's Data Analytics team and work closely with the Men's First Team Analysis department. The role involves planning, building and deploying internal products that support football analysis while translating advanced AI research into tools that coaching staff can use in their day-to-day work.
Rather than conducting research in isolation, the engineer will collaborate directly with analysts and coaches to develop data-driven applications, automate analysis workflows and identify opportunities where AI can improve existing football processes. The club says the position is intended to accelerate the adoption of proprietary technology across coaching and performance analysis.
What Arsenal is looking for
The role requires a strong quantitative background in disciplines such as computer science, data science, mathematics or statistics, alongside expertise in software engineering and machine learning.
Candidates are expected to be proficient in Python, SQL and JavaScript or TypeScript, while also having experience with deep learning frameworks such as PyTorch, JAX or TensorFlow. Familiarity with modern data science libraries and an understanding of football are also listed as important qualifications.
The successful applicant will also be expected to design scalable full-stack applications, build interfaces that present complex football insights clearly, and work in the fast-paced environment of a professional football club, including collaborating around training and matchday schedules.
AI's growing influence on football
The vacancy is another sign of AI's expanding role in elite sport. Modern football clubs collect enormous volumes of data from tracking systems, video feeds, player movement, event logs and performance metrics. Machine learning models are increasingly being used to analyse tactical patterns, evaluate player performance, optimise training loads and support in-game decision-making.
Academic research has also highlighted football as one of the fastest-growing real-world applications for artificial intelligence, with advances in computer vision, deep learning and spatiotemporal modelling enabling increasingly sophisticated analysis of players and teams.
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