Computer Vision Engineer

Vimaan is looking to a Computer Vision Engineer at its headquarters in Santa Clara to drive the development of computer vision and machine learning algorithms to power our cutting-edge wall-to-wall warehouse inventory tracking and verification platform. This is a unique opportunity to exploit a treasure cove of unseen real-world data coming from a multi-camera perception system and develop large scale computer vision and deep learning models to build a product that creates a disproportionate value for warehouse industry. The role involves hands on CV/ML software development and deployment – from understanding the product requirements, defining Computer Vision functional specs to designing, developing, and deploying CV/ML models in production at scale. The nature of certain projects requires US citizenship so that will be a must have criteria.

Computer Vision Engineer Qualifications

The ideal candidate has the following attributes:

• MS in computer vision, machine learning, AI, applied mathematics, data science, or related technical fields or BS with 3+ years experience in Computer Vision/Machine Learning
• Hands on experience in developing new learning algorithms for one or more of computer vision tasks such as object detection, object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation, adversarial and generative models etc., and representational learning with a varied amount of data – from a few samples to a very large dataset.
• Knowledge of current DL literature and the mathematical foundations of machine learning
• Ability to train and debug deep learning systems – from defining datasets and evaluation metrics, model training, deployment, failure characterization, and iterative improvement
• Strong programming skills and development experience with python and ML/DL frameworks such as Tensorflow, Pytorch etc.
• Deep insights into data characteristics and ability to map those to appropriate model architectures
• Experience working with inputs coming from multiple cameras and input modes is a plus.
• Hands on experience with MLOps tools & methods is a plus.
• Experience in AI Infrastructure, Machine Learning Accelerators, On-Device Optimization is a plus
• Highly motivated and passionate individual with a very strong work ethic, ability to work in a team and work independently under supervision and guidance in a matrix management environment
• Ability to work in a fast paced, high pressure startup environment and adapt to rapidly changing requirements.