Position: Lead Deep Learning Engineer / AI Product Manager
Category: Data Science
English level: fluent
Years of experience: 7

- Developed a framework for handling deep learning pipelines and unification of DL projects with PyTorch (model zoo and configuration, train/inference loop, serialization, evaluation, and visualizations, etc.), for both the AI engineering team and as a part of the company product.
- Delivered DL solutions in various computer vision projects without data acquisition stage, only synthetic data were used
- Developed and implemented task-oriented Domain Adaptation framework (synthetic-to-real)
- Took an active part in product development for computer vision engineers and data scientists
- Design and prototyping complex AI solutions as a team leader (delivery planning, risk management)
- Advise company leaders on recent deep learning advancements 
  in the industry and academia to further influence research 
  direction and product development,
- Develop project requirements, specifications, and POCs. 
  Communicate with stakeholders,
- Responsible for team commitment (the scope, timeline and 
  quality)
- R&D in domain adaptation/domain generalization, data-centric 
  AI, synthetic data application in AI-powered solutions
- Design, implement and support a framework for handling deep 
  learning pipelines with PyTorch (model configuration, 
  train/inference loop, serialization, distributed learning, 
  evaluation, and visualizations, etc.),
- Implementation and reverse-engineering of newly published algorithms/models architectures from top journals and conferences in computer vision,
- Implement deep learning solutions, algorithms, and tools for object detection, geometry reasoning, depth estimation, semantic segmentation, style transfer
- Hands-on expertise in synthetic approach for Deep Learning

Experience in CV sub-domains: Camera distance estimation, 3D human/object pose estimation, keypoints - 2D/3D, Semantic Segmentation, Object detection, Image-to-image translation, Domain adaptation, Representation learning.
Experience in NLP sub-domains: language modeling, text infilling, NER, text classification, and clustering. 
Professional development in a start-up environment

Preferred technologies:
Python, PyTorch, Conda, Docker, Bitbucket / JIRA / Confluence, AWS/Azur, SCRUM, English speaking team.
- I am an EU permanent resident, based in Warsaw, Poland 
- I have already registered and expect to use polish individual entrepreneurship  
- Expected compensation in my profile includes taxes in Poland, but you have to add VAT