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.
Requirements
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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What We Do
Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. Huawei's end-to-end portfolio of products, solutions and services are both competitive and secure. Through open collaboration with ecosystem partners, we create lasting value for our customers, working to empower people, enrich home life, and inspire innovation in organizations of all shapes and sizes. At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward. We have more than 180,000 employees, and we operate in more than 170 countries and regions. Founded in 1987, Huawei is a private company fully owned by its employees. House Rules This page is for ICT professionals with an interest in Huawei and our industry to engage in open discussions. To facilitate dialogue, please follow these rules: - Huawei holds the right to delete comments that are offensive, misleading, false, unlawful, off-topic and in violation of any regulations. - Repeated violations of any of the above will be removed and users may be blocked. - Huawei does not necessarily endorse the information shared by members. - Please be familiar with and follow LinkedIn's User Agreement. - By publicly uploading a photograph or comment, you give Huawei permission to feature your content. This will always be credited. Please visit the below portals for career or customer service queries. Career page: http://bit.ly/2rdljD7 Customer service: http://bit.ly/2a4mXNY Thank you for visiting us & we hope you enjoy your time on our page.
