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Get AI-powered advice on this job and more exclusive features.About the jobChampion Data has an exciting opportunity for an experienced and dedicated Senior Computer Vision Engineer to join our team!The Senior Computer Vision Engineer will innovate, design, develop, and deploy real-time computer vision systems for elite sport. This deeply technical role will contribute to officiating support technology for the AFL and offers the chance to join a worldfirst innovation project from the ground upconducting research and rapid development to deliver optical tracking products.The role spans object detection and tracking, multi-camera systems, 3D geometry, low-latency models, production-grade deployment, and MLOps.Key ResponsibilitiesDesign and implement real-time computer vision algorithms for sport in a multi-camera, latencyconstrained environment.Build robust 3D reconstruction pipelines for problems including ball and player tracking under strong occlusion and noise.Build, train and evaluate state-of-theart deep learning models for problems such as object detection, segmentation, action recognition, event detection and pose estimation.Conduct rapid experimentation to quickly validate ideas.Contribute to the development of CV/ML solutions across the entire product lifecycle, from ideation/experimentation to POC/MVP to production.Package and deploy CV models to edge and cloud compute.Monitor solutions and deploy iterative improvements based on observed performance and stakeholder feedback.Write maintainable, welltested, productionready code, and work closely with software engineers and architects to productionise successful experiments and proof of concepts.Design scalable solutions that are suitable for the resource constraints.Collaborate with a team of CV engineers, AI engineers, software developers and data analysts, and engage in weekly code/algorithm review meetings.About YouBachelor''s or Master''s degree in Computer Science, Engineering, or a related field.Publications or contributions in Computer Vision/Machine Learning research or opensource projects are highly regarded.4+ years of industry or research experience in computer vision (prior experience in sport highly regarded but not required).Strong experience with modern deep learning models for computer vision (e.g. CNNs, Vision Transformers, VAEs, GANs etc.).Experience with common computer vision paradigms including object detection (e.g. YOLO, SSD models), multitarget object tracking (e.g. SORT, DeepSORT), action recognition and pose estimation.Experience with multicamera systems, including a familiarity with projective geometry.Proven experience developing computer vision solutions in realtime or latencyconstrained environments.Expert level Python programming including strong experience with common CV/ML and scientific libraries, such as PyTorch, OpenCV, NumPy, SciPy, scikitlearn etc.Demonstrated experience working across the entire CV model lifecycle, from rapid experimentation to deployment and monitoring using best practice MLOps.Experience working with large volumes of visual data in a realtime context.Familiarity with software and MLOps best practices including version control, containerisation, and model and data traceability.Familiarity with cloud platforms a plus (e.g. GCP).Excellent communications skills and an ability to communicate with technical and nontechnical stakeholders.About Champion DataFor over 20 years, Champion Data has been at the forefront of delivering sports stats globally. With a global presence in Australia, the USA, the UK, and Asia, we specialise in realtime data collection, storage, analysis, distribution, and visualisation. We track every play and movement, delivering unbeatable game intel through seamless integration systems. Our unrivalled visual packages, in partnership with leading media outlets, ensure a sensational sports broadcast experience. We work across numerous major sports, including AFL, NRL, Football, Horse Racing, World Netball, LIV Golf, Tennis, and Lacrosse. As we continue to expand globally, we aim to solidify our position as the leading sports data company.At Champion Data, our people are at the core of our success, driving the innovation and passion that underpin our company culture. By joining our team, you will be part of a motivated group with a ''cando'' attitude, eager to embrace challenges and committed to personal and professional growth. At Champion Data we will enable you to be your own champion.Our Core ValuesTo challenge the Playbook / To be an Elite Partner / To Champion TeamWhy Join Champion Data?We offer flexible hybrid working arrangements, financial support for setting up a remote workspace and a strong focus on health and wellbeing. Our team culture is vibrant and supportive, including regular social events, team lunches, and more. We also provide extensive employee benefits, including access to our wellness program and additional leave through Mindful Me Days.Benefits (Australia)Mindful Me Days: Four days per year dedicated to your wellbeingFlexible Working: Our team works globally in a hybrid environment, which includes two weeks per year, during which you can work remotely from anywhere worldwide.AUS Office: Access to a newly renovated office in Southbank, Melbourne.Our spaces: all of our offices have great endofjourney facilities; including showers, wellness/prayer room & gamesEmployee Assistance Programs: 24/7 Access to financial support and counsellingWellness Incentive: To help support your home office setup or contribute towards a wellness activity/service of your choosingGet to the Game: Funds towards tickets for you and your family/friends to attend sporting events globally.Advance You Learning and Development: Annual budget to spend on learning and development activities plus Brain Block Time, this is time set aside monthly to learn or study.Social Events: Including an annual Family Day & Volunteer DaySeniority levelMidSenior levelEmployment typeFulltimeInformation Technology, Science, and EngineeringIndustriesSpectator Sports, Broadcast Media Production and Distribution, and Technology, Information and Media#J-18808-Ljbffr