Huawei Telekomünikasyon Dış Ticaret Ltd

Computer Vision Engineer (Senior)

Huawei Telekomünikasyon Dış Ticaret Ltd Turkey 8 days ago
engineering

About the Role

We are an Applied AI team bridging the gap between cutting-edge research and production systems. We are looking for an engineer who excels in AI model design, optimization, and real-world deployment.

In this role, you will architect solutions for complex visual understanding tasks. Your work will span robust object detection, instance segmentation, multi-object tracking, and multimodal reasoning with VLMs. Leveraging both classical computer vision and modern deep learning, you will own the full lifecycle of the model—from mathematical formulation to high-performance implementation in Python and C++.

Requirements

Who We Are Looking For

We are primarily targeting Senior level engineers. However, we are open to exceptional Mid candidates who possess a strong track record of relevant job experience or significant academic research.

Key Qualifications

Education:

  • M.S. or Ph.D. in Computer Vision, Machine Learning, or a related area.

Experience:

  • 5+ years of hands-on experience developing and deploying CV/ML models.

Technical Stack:

  • Advanced proficiency in Python and C++.
  • Strong experience with deep learning frameworks (PyTorch or TensorFlow).
  • Proficiency in debugging, profiling, and optimizing high-performance AI systems.
  • We prioritize strong theoretical knowledge of deep learning and mathematical foundations over mere framework familiarity.

Domain Expertise:

  • Deep understanding of object detection, segmentation, and object tracking.
  • Familiarity with generative models (GANs, Diffusion models) and multimodal architectures.

Foundational Knowledge:

  • Strong grasp of linear algebra, probability, optimization, and numerical methods.

Bonus Qualifications

  • Experience deploying models on edge devices or embedded systems.
  • Knowledge of secure and privacy-aware AI practices.
  • Hands-on experience with MLOps, CI/CD, and automated training pipelines.
  • A track record of academic publications (CVPR, ICCV, ECCV, etc.) or significant open-source contributions.

Why Join Us?

Real-World Impact: Work on applied research that directly enhances safety and efficiency in the physical world.

Collaborative Culture: Solve hard problems alongside a high-caliber, interdisciplinary team of engineers and researchers.

Academic & Global Growth: We actively endorse academic publications and offer opportunities to work on global projects.

Continuous Learning: We invest in your growth with sponsored access to premium online learning platforms (MOOCs) and internal technical workshops.

Compensation: We offer a competitive salary package along with a comprehensive set of side benefits.

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