Job Description
7 days ago
Our client is a leading creator of body motion video games that run on anything from mobile devices to TVs.
They are seeking a Computer Vision & ML Engineer to be part of developing indoor motion tracking technology that makes use of consumer grade hardware.
The ideal candidate should possess a scientific mindset with the ability to substantiate claims and present arguments with scientific proofs, as well as a commitment to building products that are practical, functional, and user-centric.
What you will do:
• Design, develop, and integrate a variety of ML and non-ML-based Computer Vision algorithms.
• Work with and optimize ML and CV frameworks such as TensorFlow, PyTorch, and OpenCV.
• Implement asynchronous and parallel programming patterns to enhance computational efficiency.
• Apply ML theories, numerical optimization, and image processing techniques to practical problems.
• Collaborate with cross-functional teams to translate research into real-world applications.
What you will need:
• Experience in MLOps, automation, and deploying CV applications on edge devices.
• Familiarity with physics modeling, computational geometry, statistics, and quantitative methods.
• Understanding of computer architectures, operating systems, and low-level programming
• A track record of research, publications, or deep domain knowledge in ML and CV
They are seeking a Computer Vision & ML Engineer to be part of developing indoor motion tracking technology that makes use of consumer grade hardware.
The ideal candidate should possess a scientific mindset with the ability to substantiate claims and present arguments with scientific proofs, as well as a commitment to building products that are practical, functional, and user-centric.
What you will do:
• Design, develop, and integrate a variety of ML and non-ML-based Computer Vision algorithms.
• Work with and optimize ML and CV frameworks such as TensorFlow, PyTorch, and OpenCV.
• Implement asynchronous and parallel programming patterns to enhance computational efficiency.
• Apply ML theories, numerical optimization, and image processing techniques to practical problems.
• Collaborate with cross-functional teams to translate research into real-world applications.
What you will need:
• Experience in MLOps, automation, and deploying CV applications on edge devices.
• Familiarity with physics modeling, computational geometry, statistics, and quantitative methods.
• Understanding of computer architectures, operating systems, and low-level programming
• A track record of research, publications, or deep domain knowledge in ML and CV
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