ML Engineer / Computer Vision Specialist
⚲ Warszawa
130–190 zł netto (+ VAT) / godz.
Wymagania
- Python
- TensorFlow
- PyTorch
- AWS
- Azure
- Google Cloud Platform
- Docker
- Kubernetes
Opis stanowiska
Nasze wymagania:
minimum 3 years of commercial experience in Machine Learning / AI
hands-on production experience in at least 2 Computer Vision projects
experience with fine-tuning or transfer learning of Computer Vision models
strong Python skills
practical experience with TensorFlow or PyTorch
experience working with image processing and CV pipelines
understanding of model training, evaluation, and optimization
experience deploying ML models into production environments
analytical mindset and problem-solving approach
English level B2+
Mile widziane:
experience with MLOps tools and ML pipelines
experience with cloud platforms (AWS, Azure, GCP)
familiarity with Docker and Kubernetes
experience with OCR, object detection, segmentation, or video analysis
experience working with large datasets and model optimization
O projekcie:
We are looking for an experienced ML Engineer / Computer Vision Specialist to join innovative AI-focused initiatives and work on advanced Computer Vision solutions in production environments.
Zakres obowiązków:
We are looking for someone with strong hands-on experience in developing, fine-tuning, and deploying ML models, who enjoys solving complex problems related to image processing and Computer Vision. The role involves close collaboration with engineering teams, improving model performance, and supporting end-to-end machine learning workflows.
Oferujemy:
opportunity to work on advanced AI and Computer Vision solutions
long-term cooperation
flexibility in work model (remote / hybrid)
impact on technology direction and model development
collaboration with experienced engineering teams
minimum 3 years of commercial experience in Machine Learning / AI
hands-on production experience in at least 2 Computer Vision projects
experience with fine-tuning or transfer learning of Computer Vision models
strong Python skills
practical experience with TensorFlow or PyTorch
experience working with image processing and CV pipelines
understanding of model training, evaluation, and optimization
experience deploying ML models into production environments
analytical mindset and problem-solving approach
English level B2+
Mile widziane:
experience with MLOps tools and ML pipelines
experience with cloud platforms (AWS, Azure, GCP)
familiarity with Docker and Kubernetes
experience with OCR, object detection, segmentation, or video analysis
experience working with large datasets and model optimization
O projekcie:
We are looking for an experienced ML Engineer / Computer Vision Specialist to join innovative AI-focused initiatives and work on advanced Computer Vision solutions in production environments.
Zakres obowiązków:
We are looking for someone with strong hands-on experience in developing, fine-tuning, and deploying ML models, who enjoys solving complex problems related to image processing and Computer Vision. The role involves close collaboration with engineering teams, improving model performance, and supporting end-to-end machine learning workflows.
Oferujemy:
opportunity to work on advanced AI and Computer Vision solutions
long-term cooperation
flexibility in work model (remote / hybrid)
impact on technology direction and model development
collaboration with experienced engineering teams
🔍 Dekoder Ogłoszenia
🔴
hands-on production experience in at least 2 Computer Vision projects
Może oznaczać dwa projekty, które były w fazie produkcji, ale niekoniecznie były tam długo lub miały duży wpływ.
🔴
experience deploying ML models into production environments
Może oznaczać jedynie doświadczenie w uruchamianiu modeli, a nie w całym procesie utrzymania i skalowania ich w produkcji.
🔴
analytical mindset and problem-solving approach
Często używany zwrot, który może oznaczać, że będziesz musiał samodzielnie rozwiązywać wiele problemów bez jasnych wytycznych.
🟡
opportunity to work on advanced AI and Computer Vision solutions
Może oznaczać pracę nad istniejącymi, zaawansowanymi rozwiązaniami, a niekoniecznie tworzenie od podstaw czegoś zupełnie nowego.
🟡
improving model performance
Może oznaczać drobne optymalizacje istniejących modeli, a nie znaczące przełomy w ich działaniu.