Computer Vision Engineer
Computer Vision Engineer
Posted on :
24-05-2025
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1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
24-05-2025
Job Description
Job Title: Computer Vision Engineer and nbsp;
Type and Location: Remote; Both Full-Time and Internship opportunities available
Company: RNT Health Insights Private Limited
About Us: and nbsp; and nbsp; and nbsp;
At RNT Health Insights we are developing Breakthrough Medical Devices to improve the accuracy of detecting early-stage upper gastrointestinal cancers in real-time during endoscopic procedures. We have been granted the US FDA Breakthrough Device Designation for two of our solutions- one intended for early gastric cancer detection and the other for detecting Esophageal adenocarcinoma. The technology behind our AI-assisted detection technology integrates advanced spatial and temporal computer vision algorithms and is capable of detecting even the smallest mucosal abnormalities flat lesions or color / textural changes.
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Job Description: and nbsp;
As a Computer Vision Engineer you will play a pivotal role in researching developing and implementing spatiotemporal algorithms for detecting and delineating lesions in real-time during endoscopic video feeds. You will collaborate with a multidisciplinary team of AI researchers gastroenterologists and software engineers to enhance both spatial and temporal accuracy in lesion detection. This role involves designing preprocessing pipelines optimizing models and ensuring low latency high-performance deployment in clinical settings.
Key Responsibilities: and nbsp;
- Algorithm Development: Research develop and implement spatiotemporal techniques combined with CNN and other spatial models for real-time lesion detection in endoscopic video streams. and nbsp;
- Temporal Analysis: Investigate and apply state-of-the-art techniques (e.g. LSTMs 3D CNNs) to model temporal dependencies in video-based data for improved lesion tracking and detection. and nbsp;
- Model Integration: Integrate temporal models with existing CNN-based spatial models to create efficient end-to-end pipelines for real-time inference during endoscopy procedures. and nbsp;
- Preprocessing and amp; Inference Pipelines: Design and implement robust video preprocessing (e.g. frame extraction image enhancement noise reduction) and inference pipelines that ensure smooth integration with endoscopic hardware and software systems. and nbsp;
- Post-processing Optimization: Work on post-processing techniques to improve lesion localization classification and segmentation accuracy and ensure consistent performance in different clinical settings. and nbsp;
- Model Optimization: Fine-tune models for deployment on constrained hardware platforms ensuring low-latency performance without compromising accuracy. and nbsp;
- Collaborative Research: Collaborate with research teams to explore and incorporate cutting edge temporal models multi-frame fusion techniques and domain-specific innovations in medical video analysis. and nbsp;
- Performance Benchmarking: Benchmark models against datasets assess performance (accuracy speed robustness) and optimize for real-time clinical use. and nbsp;
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Qualifications and Expectations: and nbsp;
- Bachelors/ Masters/ PhD in Computer Science Electrical Engineering or closely related fields with a focus on Artificial Intelligence Machine Learning or Computer Vision. and nbsp;
- Strong foundation in computer vision principles including image processing techniques feature extraction methodologies and neural network architectures. and nbsp;
- Proficiency with deep learning frameworks such as TensorFlow Keras or PyTorch. and nbsp;
- Proficiency in programming languages particularly Python and C with the ability to write clean efficient and well-documented code. and nbsp;
- Solid grasp of machine learning algorithms and methodologies including experience with real-time inference and model optimization for deployment in resource-constrained environments. and nbsp;
- Ability to engage with and interpret relevant scientific literature staying updated on the latest advancements in computer vision and machine learning as they apply to medical applications. and nbsp;
- Ability to communicate ideas clearly and effectively both in oral and written formats and nbsp; and nbsp;
- Self-motivated individual who works well in a team and is open to giving and receiving honest feedback and nbsp;
If you are passionate about computer vision and eager to contribute to cutting-edge healthcare technology we would love to hear from you!
Employment Type
Full Time
Key Skills
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