Computer Vision Engineer

Recex.co; Chandigarh; Remote; INR 600,000 - 1,200,000; Full time

Job summary

A healthcare technology company is seeking a Computer Vision Engineer to research, develop, and implement algorithms for real-time lesion detection in endoscopic procedures. This role involves working closely with AI researchers and medical professionals to enhance detection accuracy using cutting-edge technology in a remote setting. The ideal candidate will have a strong background in computer vision and machine learning, with proficiency in Python and deep learning frameworks.

Qualifications

• Strong foundation in computer vision principles.
• Proficiency with deep learning frameworks.
• Ability to write clean and efficient code.

Responsibilities

• Develop and implement spatiotemporal algorithms for lesion detection.
• Collaborate with teams to enhance model performance.
• Design and optimize video preprocessing pipelines.

Skills

Computer Vision

Machine Learning

Deep Learning

Image Processing

Python

C++

Model Optimization

Education

Bachelor's, Master's, or PhD in Computer Science

Electrical Engineering, or related fields

Tools

TensorFlow

Keras

PyTorch

Job description

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Job Title: Computer Vision Engineer

Type and Location: Remote; Both Full-Time and Internship opportunities available

Company: RNT Health Insights Private Limited

About Us

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 integrates advanced spatial and temporal computer vision algorithms, capable of detecting even the smallest mucosal abnormalities, flat lesions, or color/textural changes.

Job Description

As a Computer Vision Engineer, you will research, develop, and implement spatiotemporal algorithms for detecting and delineating lesions in real-time during endoscopic video feeds. You will collaborate with AI researchers, gastroenterologists, and software engineers to enhance spatial and temporal accuracy in lesion detection. Your role involves designing preprocessing pipelines, optimizing models, and ensuring low latency, high-performance deployment in clinical settings.

Key Responsibilities

• Research, develop, and implement spatiotemporal techniques combined with CNN and other spatial models for real-time lesion detection in endoscopic video streams.
• Investigate and apply state-of-the-art techniques (e.g., LSTMs, 3D CNNs) for modeling temporal dependencies in video data to improve lesion tracking and detection.
• Integrate temporal models with existing CNN-based spatial models for efficient, end-to-end real-time inference during endoscopy procedures.
• Design and implement robust video preprocessing and inference pipelines that ensure smooth integration with endoscopic hardware and software systems.
• Work on post-processing techniques to improve lesion localization, classification, and segmentation accuracy across clinical settings.
• Fine-tune models for deployment on constrained hardware platforms, ensuring low-latency performance without compromising accuracy.
• Collaborate with research teams to explore and incorporate cutting-edge temporal models, multi-frame fusion techniques, and domain-specific innovations in medical video analysis.
• Benchmark models against datasets, assess performance, and optimize for real-time clinical use.

Qualifications and Expectations

• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or related fields with a focus on AI, Machine Learning, or Computer Vision.
• Strong foundation in computer vision principles, including image processing, feature extraction, and neural network architectures.
• Proficiency with deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Proficiency in Python and C++, with the ability to write clean, efficient, and well-documented code.
• Solid understanding of machine learning algorithms, real-time inference, and model optimization for resource-constrained environments.
• Ability to interpret scientific literature and stay updated on advancements in computer vision and machine learning for medical applications.
• Effective communication skills, both oral and written.
• Self-motivated, team-oriented, open to feedback.

If you are passionate about computer vision and eager to contribute to cutting-edge healthcare technology, we would love to hear from you!

Additional Details

• Seniority level: Internship
• Employment type: Full-time
• Job function: Engineering and Information Technology
• Industries: Human Resources Services

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