Why Join Us?
- Join a rapidly growing company with $50M ARR and 250K+ happy customers across the US and Europe.
- Work with a high-caliber engineering team from companies like Lensa, Picsart, Viber, VK, and Yandex.
- Backed by investors who successfully exited companies like Looksery and AI Factory, selling to Snap for $150M and $166M, respectively.
- Contribute to cutting-edge AI technologies in entertainment applications.
About the Role
As a Computer Vision Engineer at Glam, you'll develop state-of-the-art AI-driven solutions to revolutionize video and image editing. Leveraging your expertise in computer vision, deep learning frameworks, and advanced techniques such as GANs and diffusion models, you will be a vital contributor to shaping the future of content creation technology. If you're a creative problem solver with a passion for AI and a knack for pushing the boundaries of what's possible, we want you on our team.
Key Responsibilities
- Develop and optimize algorithms for image and video processing, including stylization, enhancement, and content generation.
- Build and train machine learning models such as GANs, diffusion models, and other advanced AI techniques to improve visual effects and content creation tools.
- Collaborate with cross-functional teams (Product, Marketing, Engineering) to integrate CV solutions into user-facing products.
- Conduct performance analysis and refine algorithms for optimal efficiency.
- Stay abreast of the latest AI and computer vision trends to keep Glam at the forefront of innovation.
Qualifications
- Experience:
- Demonstrable expertise in building and deploying CV-based applications.
- Proficiency in training and implementing advanced AI models, including GANs and diffusion models.
- Experience delivering image/video processing solutions for real-time or large-scale applications.
- Technical Skills:
- Strong programming skills in Python.
- Hands-on experience with deep learning frameworks like TensorFlow or PyTorch.
- Knowledge of CV libraries and tools such as OpenCV, Mediapipe, or equivalent.
- Familiarity with cloud-based model deployment solutions.
- Additional Skills (Preferred):
- Expertise in optimizing models for mobile applications.
- Experience with large-scale datasets and real-time processing.