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Our products help to improve fan engagement, officiating acceptance, and drive commercial performance for sports leagues and federations.
We use cutting-edge technology to do a variety of amazing things with cameras and other data sources (all in real-time on site or in the cloud), including:
Tracking the 3D position of vehicles in elite motorsport (e.g. Providing the platform for sports federations to make critical officiating decisions using video and tracking data
We have a commitment to diversity and inclusion across race, gender, age, religion, and identity. We are searching for motivated, driven and proactive individuals, who will own a ML-based project, or research block to design, train and integrate a new machine learning model. The role will involve working closely with ML, software engineering and operations teams to ensure the models are well designed, integrated and utilised in our products.
Model Development, Implementation and Deployment:
Develop and implement state-of-the-art models for computer vision problems including object detection, key-point estimation, segmentation; using Python, PyTorch, Ignite, OpenCV, AWS
Research, prototype, and implement state-of-the-art machine learning algorithms
Design and implement custom loss functions, evaluation metrics, and training procedures
Evaluate model performance
Drive innovation initiatives and proof-of-concept projects
Export models to ONNX and deploy and integrate them into our C++ environment using TensorRT
Build and maintain machine learning infrastructure and deployment pipelines
Implement model monitoring and performance tracking systems
Establish monitoring, alerting, and automated retraining systems for production models
Establish monitoring, alerting, and automated retraining systems for production models
Optimize data workflows for performance and cost efficiency
Implement data and augmentation pipelines for training
Perform exploratory data analysis to identify patterns and insights
Ensure data quality and integrity throughout the machine learning life-cycle
Stay up-to-date with the latest developments in AI, model architecture and infrastructure
2-5 years of professional experience in machine learning engineering or related roles
~ Proven track record of deploying machine learning models to production environments
~ Experience leading technical projects and managing timelines
~ Experience with end-to-end ML project life-cycle from research to deployment
~ Self starter with initiative and the ability to pick up and develop projects independently
~ Experience with A/B testing and experimental design
~ Excellence with Python
Proficiency with data processing tools (Pandas, NumPy)
Experience using machine learning frameworks like PyTorch or TensorFlow
Familiarity with cloud platforms and their ML services
Mentorship from senior machine learning engineers and data scientists
Clear career progression paths within the ML engineering discipline
If you are looking for a company where you will be challenged, valued and respected, with great compensation in a team that doesnt play politics then this is the role for you
Competitive salary, depending on experience and skill set
Bonus scheme
Flexible hours and choice of working remotely
The option to travel to sporting events around the world
Having started during the Covid-19 pandemic, the majority of us work remotely from home. We also have an office in London and Winchester for those that prefer office working.
Employment type Full-time

Job function Engineering and Information Technology
Industries Software Development
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Location:
Haggerston, Greater London
Job Type:
FullTime

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