Here's what you will do:
- Researching, prototyping and reverse-engineering of ML/DL algorithms in various sub-domains of Computer Vision and Generative AI
- Experimenting with real-world data to validate, evaluate and improve the algorithms
- Testing and deployment of deep learning algorithms on embedding systems
Here’s the background we’d like you to have:
- At least 5 years experience in data science
- Proven experience in tackling common computer vision tasks including image classification, detection, segmentation, face recognition, pose estimation, etc. & familiarity with popular architectures such as Vision Transformers, DeepLabv3, SegFormer, etc.
- Good command of deep learning framework PyTorch
- Solid knowledge of machine learning techniques and probability theory
- Experience in machine learning model deployment in a business setting
- Good command of Python and use of pertinent libraries for data analysis and machine learning like numpy, scipy etc.
- Working knowledge of version control systems like Git and SVN
- Creativity, good imagination and statistical thinking
- B2+/C1 level of English
Nice to have:
- Experience with Generative AI
- Team leadership skills
- Experience in CV sub-domains: Camera distance estimation, 3D human/object pose estimation, key points - 2D/3D, Semantic Segmentation, Object detection, Image-to-image translation, Domain adaptation, Representation learning.
- Hands-on experience with GAN (DC-GAN, CycleGAN, Pix-to-Pix and others), Wassertain-GAN, VAE, U-net, MaskRCNN, Yolov2/v3
- Technical writing skills
Work Methodology:
- Code reviews, SCRUM
- Build server – GitLab
- Conda, Docker, Bitbucket / JIRA / Confluence
- AWS / Azure
- Operating System – Linux
Benefits:
- Sport subscription
- Private healthcare
- Training budget
- International conferences
- Modern Office, no dress code & young team
- Bonus policy