Our compensations (cash and equity) are determined based on the position, your location, qualifications, and experience.
Responsibilities:
Develop Bird’s Eye View (BEV) perception models for autonomous driving applicationsDevelop Vision Language Models for scene understanding and action generation for autonomous driving applicationsComplete ownership of project from ideation, design, developing data requirements, model training, evaluation and deploymentResearch 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 environmentsRigorous 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 field3+ years of industry experience working on cutting edge deep learning applicationsExpertise with Python, willingness to do some C++ development as needed.Deep understanding of machine learning principles and methodologiesExperience 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 learningIn-depth understanding of cutting-edge deep learning techniques and architectures like transformers, CNNsExpertise 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
