Senior Engineer / Module Lead (DL, Computer Vision, IP) - Work From Office - 5 days a week

AIRA Matrix; Thane; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

AIRA Matrix invites applicants for an AI/ML focused role to design and implement real-time image analysis and classification algorithms for pathology and related life sciences applications.

The position emphasizes development of segmentation, detection and quantification methods for ultra-high-resolution images, with emphasis on efficient ML/DL models and hands-on coding across C/C++/Python/Java. Collaboration with a talented team is essential.

Qualifications

• Hands-on experience in image processing and ML algorithms.
• Strong programming skills in C, C++, Python, Java.
• Experience with medical image processing is an advantage.

Responsibilities

• Design and develop real-time algorithms for analysis and classification of medical images.
• Develop solutions for segmentation, detection, classification and quantification of high-resolution pathology images.
• Design efficient ML/DL models for accurate analysis and classification.
• Learn and apply emerging tech trends to projects for better results and potential publications.
• Explore expert systems, cognitive computing and computational photography.
• Guide the team technically.

Skills

Image Processing

Machine Learning

Deep Learning

GPU Parallel

C/C++/Python/Java

Education

PhD/M.Tech/M.E./M.C.A.

B.Tech/B.E.

Tools

Deep Learning Frameworks

Job description

AIRA Matrix provides artificial intelligence based solutions for Life Sciences applications. Our solutions improve efficiency, diagnostic accuracy, and turnaround times in pathology, microbiology and ophthalmology workflows across pharmaceutical and healthcare laboratories.

Our Application Development Team plays an important role in developing competent customer facing applications to access our AI solutions and enterprise-level image management systems in life sciences.

It has successfully developed several innovative solutions, such as a one-of-a-kind image viewing platform for histopathology images enabled with digital collaboration, custom web applications with built-in workflows for microbial monitoring, and custom libraries for UI to support unique features and audit traceability across applications among other functionalities.

With absolute flexibility to choose and use the latest technologies, our AppDev team comes up with best-in-class enhancements and feature upgrades which are highly appreciated by the customers.

Job Description:

• Design and development of robust, efficient and real-time algorithms for Analysis and Classification of Medical Images using state-of-art techniques from Image Processing, Pattern Recognition, Computer Vision and Machine Learning.
• Development of innovative solutions for various problems related to Segmentation, Detection, classification and quantification of high resolution (~50K x 50K) coloured images for applications in Digital Pathology.
• Design of efficient models in Machine Learning / Deep Learning for accurate analysis and classification of High resolution Images.
• To learn and update oneself on the emerging trends of technology and apply them in the projects for better results leading to publications and patents.
• Explore new areas of Expert Systems, Cognitive Computing, Artificial Intelligence, Computational Photography etc.
• Guiding the team technically

Candidate Profile:

Academic background:

• PhD / M. Tech. / M.E. / M.C.A. (preferably from CSE / IT / ECE / EE background)
• B. Tech. / B.E. with exceptional academic/professional background

Specialization / Domain knowledge:

• Experience with Medical Image Processing is an added advantage

Technical

• Hands-on experience in developing and implementing Image Processing and Machine Learning algorithms
• Strong programming knowledge in any of C, C++, Python, JAVA etc.
• Hands-on experience in using Deep Learning frameworks and libraries
• Concepts of parallel architecture on GPU is an added advantage

Regards,

Deputy Manager - Talent Acquisition