At a Glance
- Tasks: Join us to develop innovative computer vision solutions for elite sports performance.
- Company: Catapult, a leader in sports performance technology, transforming the industry since 2006.
- Benefits: Collaborative culture, global team, and opportunities for personal and professional growth.
- Other info: Work with diverse teams across 20+ countries and contribute to global sports analytics.
- Why this job: Make a real impact on athletes' performance while working with cutting-edge technology.
- Qualifications: Passion for computer vision and experience with deep learning frameworks like PyTorch or TensorFlow.
The predicted salary is between 59400 - 72600 £ per year.
Catapult is building the future of sports performance technology, with a mission to unleash the potential of every athlete and team on earth. We are actively changing the sporting industry. Since 2006, our solutions have been leading the way in sports performance software, science, and data, where 1% can literally mean the difference between winning and losing. We work with over 5,000 teams around the world, empowering coaches, managers, and trainers in premier teams across various leagues. We provide the information they need to optimise athletes’ health, game-day readiness, and performance, as well as in-game tactics.
We are looking for an enthusiastic, inquisitive, full-lifecycle Computer Vision Engineer to join our centralised, multi-disciplinary Data Science team. This role is designed for a unique technical practitioner who enjoys owning the complete lifecycle of a feature. Working collaboratively with various stakeholders, you will help translate product briefs into algorithmic solutions, train deep learning models, engineer algorithmic pipelines, and deliver optimised, production-ready deployable artefacts that power analytics used by professional sports teams and elite athletes around the world.
What You’ll Do
- End-to-End Pipeline Contribution: Collaborate with senior data scientists, computer vision engineers, and vertical teams to translate product requirements into practical computer vision solutions.
- Algorithm & Model Development: Design, train, and evaluate deep learning architectures alongside classical computer vision pipelines.
- Geometric Computer Vision: Develop robust mathematical pipelines for camera calibration, homography estimation, and coordinate mapping.
- Modern Cloud & Containerised Deployment: Focus on architecting and containerising Python-based cloud microservices.
- Desktop Applications Support: Assist in compiling cross-platform native binaries or shared libraries.
- Automated Data Curation: Help build intelligent, automated data-ingestion pipelines.
- Interface & Boundary Design: Participate in defining clean API boundaries and interface contracts.
What You’ll Need
- Core Algorithmic Background: Foundational knowledge of classical computer vision and modern deep learning architectures.
- Production Model Training: Experience sourcing, structuring, training, and benchmarking deep neural networks.
- Hybrid Language Skills: High proficiency in Python and practical capability to read, build, and debug existing C++ codebases.
- Execution Graph Optimisation: Familiarity with optimising model runtimes and inference execution graphs.
- Modern Infrastructure: Practical experience with Docker containerisation, version control, and cloud platform execution.
NICE TO HAVE
- Neural Architecture Customisation: Experience modifying or designing custom neural network components.
- Advanced Mathematical Foundations: A strong intuitive grasp or academic background in applied linear algebra and matrix calculus.
- Downstream Integration: Experience with native application development tools.
- Sports Video Benchmarks: Experience experimenting with open-source sports analytics datasets.
- Domain Alignment: A genuine interest in sports analytics, tracking technology, or elite human performance.
What Your Success Will Look Like
- In 6 Months' Time: Your work will be contributing to features underpinning informed decisions made by elite coaches and professional athletes globally.
- In 12 Months' Time: You will reliably manage the full lifecycle of core computer vision and data science pipelines.
WHY CATAPULT?
- We have amazing people and promise you’ll work with some of the most ambitious, intelligent people in an exciting industry.
- We encourage constructive, open, and honest communication.
- We work in a collaborative yet challenging environment to consistently improve our performance.
- Our workforce spans more than 20 countries, providing opportunities to work with diverse cultures.
- We value improvement and development, maintaining a growth mindset in everything we do.
Research shows that while men apply for jobs when they meet an average of 60% of the criteria, women and other marginalised groups tend only to apply when they check every box. So if you have what it takes, but don't meet every single point in our job ad, please still get in touch!
Computer Vision Engineer employer: Catapult
At Catapult, we pride ourselves on fostering a dynamic and inclusive work culture that champions innovation and collaboration. As a Computer Vision Engineer in our London office, you'll be part of a passionate team dedicated to transforming sports performance technology, with ample opportunities for professional growth and development. Join us to make a global impact while working alongside some of the brightest minds in the industry, all committed to unleashing the potential of athletes and teams worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Computer Vision Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Catapult!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Computer Vision Engineer at Catapult.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Catapult.
✨Apply Directly through Our Website
When you find a suitable opening like Computer Vision Engineer at Catapult, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Computer Vision Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Catapult, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Catapult. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Catapult
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Catapult!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
