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

İzmir, Aegean Region, 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, Instance Segmentation, Multi-Object Tracking, Multimodal Reasoning, MLOps, CI/CD, Generative Models, Linear Algebra, Probability, Optimization, Numerical Methods

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 multi-object tracking. You will own the full lifecycle of the model from mathematical formulation to high-performance implementation.