Develop Vision Language Models for scene understanding and action generation for autonomous driving applications
Complete ownership of project from ideation, design, developing data requirements, model training, evaluation and deployment
Research and prototype novel solutions which can help tackle the long-tail of real-world problems in challenging and diverse scenarios (e.g. on highway and local roads, extreme weather conditions, sensor failures, etc)
Collaborate cross-functionally to ensure model development keeps a real-time focus and operates efficiently in compute-constrained environments
Rigorous approach to model development: running well-designed experiments, defining suitable training and validation datasets, and evaluating on the right metrics
Required Skills:
MS or PhD in CS, EE, mathematics, statistics or related field
3+ years of industry experience working on cutting edge deep learning applications
Expertise with Python, willingness to do some C++ development as needed.
Deep understanding of machine learning principles and methodologies
Experience with implementing deep learning models in at least one deep learning framework (PyTorch, Tensorflow, Jax)
Preferred Skills:
Relevant industry experience (prior work on self-driving vehicles, autonomy, computer vision and/or robotics projects)
Past experiences in deep learning projects involving object detection, motion tracking or semantic segmentation, vision-language models, end-to-end learning
In-depth understanding of cutting-edge deep learning techniques and architectures like transformers, CNNs
Expertise in machine learning or related field demonstrated by patents or publications in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH)
Experience with ML Ops and best practices for scalable ML deployment
$180,000 - $250,000 a year
Our compensations (cash and equity) are determined based on the position, your location, qualifications, and experience.
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