Second Spectrum is a Sports Emmy-winning data & tech company that is building the next way of seeing sports by capturing the highest quality data for many of the world’s largest leagues and media partners such as the NFL, NBA, MLS, English Premier League, FIBA, the NCAA, Amazon, and CBS Sports.
We are pushing the boundaries of deep tech -- machine learning, computer vision, big data, augmented and virtual reality. Our passion for cutting-edge design and decades of experience playing college and professional sports is an equal part of the magic that brings unique and innovative products to life. These products have helped Second Spectrum partners to multiple NBA championships, to win matches on football pitches around the world, to entertain and educate millions of fans on TV and digital. We're just getting started.
In 2021, Second Spectrum was acquired by Genius Sports, the official data, technology, and broadcast partner that powers the global ecosystem connecting sports, betting and media.
The Role: Computer Vision Engineer
We are looking for a production-oriented, computer vision engineer to design, develop and implement computer vision and machine learning cutting-edge technologies to ensure our market-leading position in sports player tracking and broadcast solutions.
What You’ll Do:
Design, prototype, implement and test software and computer vision & machine learning algorithms in Rust, Python, and C++.
Develop and optimize real-time and high-accuracy sports solutions with modern CV: object detection, recognition and tracking, camera calibration, 3D reconstruction, etc.
Manage interdisciplinary projects in collaboration with different groups within the company.
Implement and provide best-practices for maintainable software development, including deployment process, documentation, and adherence to and improvement of coding standards.
Leverage Amazon Web Services (EC2 and S3) to run algorithms on a large number of servers in the cloud.
Support and monitor live systems, including on-call rotation for computer vision systems during sports seasons.
Continuously learn new applications and apply learnings to new challenges.
Our Software Stack:
Main programming languages: Python 3, Rust, modern C++
Frameworks: OpenCV, CUDA, FFmpeg, Tensorflow, NumPy, scikit-learn
Codebase: Git with GitLab
Infrastructure: AWS (EC2, S3), Docker, Linux
Productivity: Slack, Notion, Google Appsequirements
What You Have:
2+ years of industrial experience in the full development life cycle: design, prototype, implementation, testing, and performance evaluation of software
2+ years of industrial experience in computer vision and modern machine learning algorithms, such as deep learning
BSc or MSc in computer science or a related degree, with strong software engineering and modern computer vision components
Solid experience in software engineering: modern software development practices and tools, concurrent and distributed programming, operating systems, computer networks, database systems
Fully proficient in Python and modern C++ with exposure to functional & object-oriented programming paradigms. Other languages such as Rust will be considered as an advantage for some of our multidisciplinary projects.
Experience with high-performance computing, GPU computing, and real-time systems would set you apart
Our Work Environment and What You Will Benefit From:
Cutting-edge products to work on for major professional sports leagues and teams.
Team-oriented engineering habits and software engineering best practices (readable, maintainable, and efficient code).
Flat hierarchy and collaborative management led by highly-qualified technical leads.
Innovative and dynamic environment, which encourages self-development and opportunities to make an impact.
Multicultural team with employees based across several countries.
Flexible working hours and 25 annual vacation days.
Attend international CV conferences (e.g. ICCV or CVPR); discuss papers on a regular basis.
As a general approach, we interview for aptitude over specific technologies or languages. Please be prepared to speak to anything listed on your resume or in your portfolio.
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