Senior Computer Vision Engineer - AI

Roles and Responsibilities :

• As a Computer Vision Engineer, you’ll be working on several areas like Visual Recognition, Segmentation, Feature Extraction/Representation Learning.
• You’ll be responsible for creating image and video based deep learning systems and making them production ready., etc.
• At Level AI, you’ll get your hands on millions of images and respective text data. Your job is to use this data and extract information from the data.
• Work within the Engineering Team to design, code, train, test, deploy and iterate on enterprise-scale machine learning systems.
• You will work with various stakeholders to understand their business requirements.
• Formulate the appropriate predictive solutions leveraging statistical and machine learning tools.
• Prioritizing tasks and taking ownership with efficiently managing project timelines and deliverables.
• Help shape the product roadmap and execute the modeling at scale.
• Researching on SOTA models and implementing the models on the current data.
• Collaborate with a cross-functional team to integrate computer vision technology into products and services.

Requirements :

• A Bachelors/Masters/PhD degree in Computer Science, Information Technology, Electrical Engineering, Statistics or related field from Tier-I college.
• Must have hands-on experience with computer vision tasks on video streams/recordings.
• Solid 3+ years of experience in building Deep Learning models for Computer Vision tasks.
• Strong theoretical knowledge of Computer Vision tasks - detection, segmentation, action recognition etc. along with recent advancements in Vision Transformers and Large Vision Models.
• Good to have deploying and scaling deep learning solutions for Computer Vision tasks with Docker and Kubernetes (Optional).
• Proficiency with Deep Learning/CV frameworks: PyTorch, torchvision, openCV etc.
• A deep understanding of computer vision, machine learning, and deep learning concepts and the ability to improve current models through finding the right area of improvement.
• Strong problem-solving skills with the ability to think from the first principles.
• A thorough understanding of the mathematics behind the various deep learning algorithms.


Preferred skills, but not a must-have:
• Worked on projects that involved multimodal machine learning (for example, text+image classification).
• Worked on projects that included feature extraction from images and a good understanding of clustering and distance metrics.
• Experience in Self-Supervised and Semi-Supervised learning.


So, if you are someone who is passionate about AI and has a strong desire to work in a fast-paced, dynamic environment, with an ability to demonstrate the ownership capabilities, we strongly encourage you to apply.