Computer Vision Engineer
Computer Vision Engineer
Posted on :
02-08-2025
Employer Active
1 Vacancy
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Job Description
About the Role
We are looking for a talented Computer Vision Engineer to design implement and deploy advanced vision-based systems that power real-world applications. This role offers the opportunity to work with cutting-edge deep learning models and collaborate with experts across multiple domains.
Key Responsibilities
- Design and develop computer vision algorithms for object detection segmentation tracking pose estimation and more.
- Implement and optimize deep learning models using PyTorch TensorFlow and OpenCV.
- Prepare datasets conduct model training fine-tuning and performance evaluation on real-world data.
- Deploy computer vision models to cloud and edge environments using tools like ONNX TensorRT and Docker.
- Collaborate with backend and infrastructure teams to integrate vision models into scalable applications.
- Stay up to date with the latest research in computer vision and apply relevant findings to production.
- Participate in code reviews contribute to architecture design and help maintain high-quality technical documentation.
Required Qualifications
- Bachelors or Masters degree in Computer Science Electrical Engineering or a related field.
- 2-4 years of professional experience in computer vision and deep learning.
- Proficiency in Python and/or C with solid experience using PyTorch TensorFlow and OpenCV.
- Strong understanding of CNNs vision transformers and modern computer vision architectures.
- Familiarity with model optimization and compression techniques.
- Hands-on experience with deployment tools such as Docker REST APIs ONNX and TensorRT.
Nice to Have
- Experience with edge deployment on devices like Jetson Nano Coral or mobile platforms.
- Exposure to MLOps tools CI/CD for ML pipelines or cloud platforms (AWS Azure GCP).
- Familiarity with SLAM OCR 3D vision or multimodal ML approaches.
Whats Offered
- Above industry-standard compensation packages.
- Comprehensive medical insurance coverage.
- Funding for higher studies and professional qualifications.
- Opportunities for rapid career growth in a global and innovation-driven environment.
- Remote-first flexible work setup that values autonomy and creativity.
Employment Type
Full Time
Key Skills
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