Computer Vision Engineer (Mid-Level) at Huawei Technologies Co. Ltd - Singapore

Ankara, Ankara, Turkey -

Full Time

Start Date

Immediate

Expiry Date

23 Mar, 26

Salary

0.0

Posted On

23 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Deep Learning, Python, C++, Object Detection, Segmentation, Multi-Object Tracking, Mathematical Formulation, Optimization, Debugging, Profiling, Generative Models, MLOps, CI/CD, Numerical Methods, Linear Algebra, Probability

Industry

Telecommunications

Description

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++. Who We Are Looking For We are primarily targeting Mid-level engineers. However, we are open to exceptional Junior candidates who possess a strong track record of relevant internships or significant undergraduate academic research. Key Qualifications Education B.S. in Computer Science, Software Engineering, Electronics Engineering, or a related field. Preferred: M.S. in Computer Vision, Machine Learning, or a related area. Experience: Mid: 3–5 years of hands-on experience developing and deploying CV/ML models. Junior: Must demonstrate solid internship experience or participation in rigorous academic studies/labs during undergrad. 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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Responsibilities

You will architect solutions for complex visual understanding tasks, spanning robust object detection, instance segmentation, and multimodal reasoning. You will own the full lifecycle of the model from mathematical formulation to high-performance implementation.