Leben=Life (German)

We are an Artificial Intelligence (AI) solutions company with focus on improving quality of diagnosis and care across areas of life sciences.

About Us

Making Artificial Intelligence easy !!

At Leben Care we make artificial intelligence work for improving diagnostic outcomes. Our approach is to enable users – practitioners, patients, researchers access our solutions in a manner that is easy and convenient.At Leben Care we are developing algorithms applying machine learning and computer vision, with focus on enabling access to data driven, more accurate diagnostics to all. Our focus at Leben Care is to extend our solutions to all forms of life –Humans, plants and animals.

Netra AI

Our flagship offering Netra AI is a platform that offers single interface access for processing retinal scans, reading them and grading them for Diabetic Retinopathy, Diabetic Macular Edema , Glaucoma and ARMD. Our mission is to make detection of preventable blindness fast, accurate, easy and available everywhere.Our solution for diabetic retinopathy is already in trials with clinical establishments.


Non Referable DR


Referable DR


There are 422 Mn+ Diabetics worldwide,  a Global Epidemic. One third of diabetics have signs of DR .Diabetic Retinopathy causes blood vessels in the retina to become fragile and leak. Its is an leading cause of preventable blindness worldwide as per WHO. Studies have demonstrated that early detection and treatment of DR helps reduce blindness and vision loss. We have built an deep machine learning based , screening solution for Diabetic Retinopathy (NETRA-DR), which classify the case as “Referable DR” or “Not Referable DR”.

NETRA-DR is under clinical validation with leading ophthalmology hospitals in India.


Non Referable DME


Referable DME


Diabetic Macular Edema (DME) or Diabetic Maculopathy (DM) is a condition characterized by the appearance of exudates on close to the macula which effects the central vision of the patient . DME usually develops at any time during the progression of Diabetic Retinopathy (DR).NETRA-DME solution which will help in early diagnosis of the disease.

NETRA-DME is under clinical validation with leading ophthalmology hospitals in India.


Our team contribution to life sciences.


Glaucoma is a chronic and irreversible neuro-degenerative condition that is one of the leading causes of preventable blindness in the world.In European countries glaucoma is the second main cause of blindness.This disease is a consequence of an accumulation of aqueous humor in the eye due to a defect of its drainage system.This condition progressively elevates the intra-ocular pressure (IOP), affecting the optic nerve and resulting impermanent blindness if left untreated.
As glaucoma may be asymptomatic in its early stages, at least half of patients with this eye pathology remain undiagnosed, while more than half of those who are undergoing treatment do not have the disease.
Our research aims to use AI and deep machine learning to understand and detect glaucoma.


Age-Related Macular Degeneration (AMD) is a progressive eye disease which damages the retina and causes visual impairment. Detecting those in the early stages at most risk of progression will allow more timely treatment and preserve sight. Without a straightforward, reliable way to screen for these vulnerable patients, early detection and treatment will remain a problem.

Our research aims to use AI and deep machine learning to understand and detect AMD.


The Team


Parthasarathy , Founder and CDO

Pat, has around 16+ years of experience in areas of Entrepreneurship, Enterprise Technology, Architecture Management and Client Management across different International Geographies. As Project Manager, he was responsible for design and development of the state of the art Applications for various verticals, globally.

Prior to Leben, Pat was providing the leadership and handling operational & strategic initiatives at Glueck Technologies Sdn. Bhd. as a founder & COO in KL, Malaysia. He has also received “Rajiv Gandhi Excellence Award” from International Business Council, New Delhi, India.


Imran Akthar , Founder and CTO

Imran Akthar is a technopreneur , having  more than a 15+ years of experience in IT Industry. He is an engineer, innovator and technologist. He has diverse background in consumer electronics, embedded software and mobile product development . He maximizes value from the fast-changing and dynamic technology ecosystem; and leveraging emerging technologies to bring the newest ,path breaking innovations to markets. Prior to Leben, he was inventor , cofounder and CTO of Glueck Technologies ,leading product development in field of AI , deep machine learning and computer vision . He also had a brief stint as an entrepreneur, having founded a startup (Sanasi) in the Mobile domain during 2010.Prior to Sanasi he managed product development for Nokia, Finland on their Mobile DRM. He is a certified PMP and  Scrum Master.


Nimish Parekh , Head of Strategy and Governance

Mr.Nimish R Parekh is a serial healthcare entrepreneur and  investor based in Singapore. He is currently a Non Executive Director on the board of UnitedHealth Care Parekh TPA and is advising several other companies in Healthcare space.He is extremely interested in how technology is shaping the future of healthcare and insurance and works closely with several companies in this area.

Mr.Parekh has successfully set up companies and built them to scale. He continues to remain involved in the JV he set up of his company with a Fortune 10 company.

Besides the above Mr.Parekh also heads his foundation Healing Fields which is recognized as a pioneer in the area of Healthcare financing and healthcare education. The foundation works with other NGO’s, private sector healthcare players and government in facilitating access to healthcare to the under privileged.


Longlong Yu , VP-Data Scientist

Long is a computer vision and machine learning scientist. He received Bachelor in Telecommunication Engineering of the University of Vigo in Spain in 2011. He graduated in Master of computer vision and artificial intelligence in Universitá de Autonoma de Barcelona in Spain in 2013. At Leben, he develops medical image analysis applications based on computer vision and deep machine learning techniques.


Gurunath , Chief Architect

Gurunath is an technical strategist  and the platform architecture in field of Computer Vision ,Embedded Hardware  and Machine Learning . Prior to  Leben, he was associated with Infosys and Polaris.



Dr. Rajesree Parekh , Clinical Advisor

Dr.Parekh is a Senior Executive with nearly 2 decades of experience in clinical, managerial and consulting roles. She is an Ophthalmic Surgeon by qualification and brings a unique experience of clinical domain coupled with leading large business roles in India and Asia. In her previous role she was leading the benefits consulting practice for Towers Watson, one of the largest consulting company in the world.Besides her clinical expertise, Dr.Parekh is also helping Leben Care adopt best clinical practices and validation protocols, helping connect with leading practitioners in the field to ensure robust product development approach


Dr. Bala Kumble  , Technology Advisor

Dr. Kumble is the Managing Director of Innova Sierra Pty Ltd which is an AusIndustry (Australian Government) registered Innovation and R&D Company providing specialist R&D advice and management, Product development – concept to product release, and Innovation advice to Industry. Innova Sierra is currently engaged in innovation in Biotechnology, Bioinformatics, Telecommunication, Mining and Industrial Automation and Smart Grid initiatives.

Dr Bala Kumble was the Chair of the Victorian Section of the IEEE and Chair of the Communication Society Chapter. Dr Kumble is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), Member of Australian Institute of Company Directors, holds PhD (Telecommunications), M.Tech (Communication Systems) and BE (Electronics & Communications Engineering) degrees. Dr Kumble has contributed extensively to Telecommunications Standardisation in ITU in Intelligent Networks, Universal Personal Telecommunications (UPT – Unified Communications), Mobile GSM Standardisation Working Groups, Dr Kumble has published several papers and contributed to Patents, and was responsible for proposing and developing the concept of Universal Personal Telecommunications, what is currently known as Unified Communications.

Dr Kumble was awarded the IEEE Millennium Medal for outstanding contributions. Dr Kumble is based in Melbourne, Australia.


We are putting together a world-class research and development team to build a platform enabling next generation of medical imaging diagnostic.

Desired qualifications

Master’s Degree or PhD – Computer Science, Artificial Intelligence or related background.

About You

You have experience in implementing best breeds of deep learning architectures.

You have an important track record as a researcher in machine learning and have published impactful journal papers.

Experience and mastery of scientific programming and libraries relevant to your field for example: Theano, TensorFlow, Caffe , Lasange , Keras ,NumPy etc.

Experience with at least one of the following programming language: Python, C++.

Experience in delivering high-quality production code and continuously learning the best practices to turn research into delightful products.

Staying up-to-date on the scientific literature in your field, and even contributing to it by publishing in famous journals and conferences.

Proven and demonstrated implementation skills (putting theory into practice).

Self-driven energetic, creative and ability to work in international teams.

Once you are here you will

Your primary mission is to put machine learning algorithms into practice, while growing your own expertise in machine learning.

Implement novel algorithms in Computer vision techniques; deep learning and applications of machine learning on images and videos.

Keep up to date with the cutting edge of deep learning, and transition those techniques to the medical domain.

Design and build novel models to solve unique medical problems.

Leading a team of data scientists delivering AI based products for improved patient outcomes.


Python, Machine Learning, Statistics, Deep Learning

What we offer for your valuable work:

Highly dynamic, innovative, passionate, intrapreneurial team

Employee Stock Option Plan


Hyderabad, India

How to Apply

Please send a cover letter and resume to hr@leben.ai. Please put “Principal Machine Learning Engineer” in the subject line.

Leben Care is offering 3/ 6/ 9 month internships  in the areas of deep machine learning and computer vision . The internships will require novel research as well as development for solving challenging problems . We are seeking qualified and highly motivated graduate students (Masters, PhD) interested in working on these problems.

The interns will have an opportunity to work on large public domain datasets; publish in top-tier conferences such as CVPR, ICCV, ECCV, NIPS, ICML and SIGGRAPH; work with business-proprietary use cases and datasets leading to inventions and patents.

Qualifications/ Experience

  • A BS/ MS degree in Computer Science, Electrical Engineering or related field.
  • Hands-on experience in machine learning / computer vision . Prior publication record in relevant top-tier conferences/ journals highly desirable.

Technical Skills

  • Proficiency in C, C++, Python. Experience using OpenCV, Caffe, Theano / Torch.
  • Experience on application development in Linux/ Windows desirable.

General Skills

  • Excellent communication, problem-solving and analytical skills, ability to learn quickly.
  • A strong passion for empirical research and for answering hard questions with data.
  • Ability to work both autonomously and in a team.

Number of Positions



Hyderabad, India

How to Apply

Please send a cover letter and resume to hr@leben.ai. Please put “Machine Learning Intern” in the subject line.

Partner with us

Partnering with clinicians helps us identify the most relevant problems, and create real-world solutions. Much of our research is done in collaboration with hospitals, universities and research institutions. If you are a medical institution and would like to partner with us on a deep learning solution, please reach out.

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