About the Role
The ML Perception role at Teleo is responsible for developing machine learning-based methods to understand and interpret scenes using various sensor modalities. This critical information enables our path-planning systems to safely navigate and avoid obstacles.
Responsibilities
- Work with the ML team to improve existing as well as implement new perception features within our systems.
- Stay abreast of the latest research by reading and implementing state-of-the-art methods from academic papers.
- Regularly communicate progress, challenges, and achievements to the team.
- Contribute to the advancement of the field by publishing research papers and filing patents.
Minimum Qualifications
- Ongoing/completed Ph.D. or Master’s degree in Computer Science or a related field. Bachelor’s degree in Computer Science or a related field with exceptional skills can be considered as well.
- Proficiency in Python and PyTorch.
- Solid understanding of neural networks and machine learning fundamentals.
- Experience with a vision-based deep learning project.
- Strong enthusiasm for continuous learning, including reading academic papers and participating in discussions about current trends in computer vision.
Preferred Qualifications
- Experience with perception projects involving cameras and/or lidar for tasks such as object detection, scene segmentation, depth estimation, freespace estimation, etc.
- Experience with Vision-Language Models (VLMs) and/or Large Language Models (LLMs).
- Good understanding of calibrating fisheye cameras using advanced models like the double sphere camera model.
- Proficiency in C++.
- Experience with version control systems, particularly Git.
- Authorship or co-authorship of papers presented at conferences like CVPR, NeurIPS, IROS, etc.
- Self-motivated and capable of planning and completing tasks independently.
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