Applied Computer Vision Engineer- Automated Driving

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