Welcome to Level AI – a Series C startup in Mountain View, CA, transforming the Customer Experience landscape with top-tier VC support and Silicon Valley expertise. Our mission: revolutionize customer sales experiences through cutting-edge speech AI, NLP/NLU, and information retrieval systems. Empowering contact center stakeholders with real-time insights, our tech facilitates data-driven decision-making for contact centers, enhancing service levels and agent performance. As a vital team member, you'll work on high-impact projects shaping the future of AI-driven enterprise applications alongside experts from Amazon, Facebook, Google, and more. At Level AI, expect a dynamic journey of fun, learning, and growth. Ready to redefine possibilities? Join us! Position Overview: As a Senior Computer Vision Engineering, you will be responsible for the Research and Development of computer vision based solutions .Some of the key areas our team is actively working to build novel capabilities include - Transformers and Generative AI, Neural Architecture Search, Large Vision Models and Core Computer Vision. We are looking for driven individuals who can help us build cutting-edge solutions for a variety of vision problems across industry verticals, especially for spatio-temporal analysis of video streams such as summarization, segmentation, etc. Competencies: Python, Computer vision, Deep learning, Machine learning, Coding, Problem solving, Communication
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.
