Applied Computer Vision Engineer- Automated Driving

Job Description

Requirements Strong technical background: At least a Bachelors/Master of Engineering in Computer Science or Electrical Sciences or related areas with 4 years of industry experience in designing and implementing vision-based algorithms [prior knowledge of working with deep neural networks is a strong plus]. Skilled software engineer with experience in Python/C++ coupled with strong problem-solving skills. Passionate about solving real-world problems: Ideally worked on autonomous driving systems before. A team player: You take ownership and work with the team to deliver exceptional results. Ability to build and iterate quickly (AGILE mindset). You enjoy working in a fast-paced environment, and you are comfortable in all stages of a product development cycle. Good hands on: You like working with production grade machine learning pipelines, from dataset curation all the way till training, validation & deployment. Good communication skills: You are able to explain technical solutions clearly to all stakeholders. You have experience writing clear, concise, and detailed documentation. Skills Strong knowledge in DL (3yrs min): Computer vision (object detection, segmentation, depth estimation), Sensor fusion (camera, radar, LiDAR), Supervised & Self-supervised learning & Transfer Learning, CNNs and transformers, Real-time model deployment and optimization, Data augmentation and annotation, Scene understanding and 3D perception, Active learning and Semi-automated data annotation techniques Hands on experience in Full stack Vision/Image related projects in production (3yrs min) Data: Visualization, Data preparation, Data handling, Data analysis & deriving insights Model frameworks: Tensorflow & PyTorch Deployment: Docker, Kubernetes Cloud deployment: Azure/AWS Other skiils: Git, Linux, Cuda, OpenMP, Distributed systems Qualifications B.E/B.Tech