You are responsible for
- Good knowledge and hands-on experience in Computer Vision, Reinforcement Learning with Q-Learning, DPO, Inverse Reinforcement learning, Behavioural cloning and Imitation Learning. Advanced generative AI models like GANS – generating medical images and Ground Truth.
- Implement and improve quality assurance processes for increasingly complex data labelling, driving the optimization of annotation processes.
- Work directly with engineers and Medical algorithms leadership. Own annotation policies that require an understanding of both technical and operational constraints.
- Proficiency in standard workflow software (GIT, Azure DevOPs, JIRA, Agile Way of working, etc.)
- Proven track record executing and meeting sensitive deadlines with limited resources
- Agile Way of working
You are a part of
Philips Research is a global organization that helps Philips introduce meaningful innovations that improve people’s lives. We provide technological options for innovations in health and well-being, targeted at both developed and emerging markets. Positioned on the front-end of the innovation process, we work on everything from spotting trends and ideation to proof of concept and – where needed – first-of-a-kind product development.
Research India is a key lab, developing innovative concepts and solutions in the areas of healthcare, informatics, cardiology, oncology, pregnancy, and parenting. These are enabled by advanced pattern recognition, deep learning, and AI technologies to modernize clinical diagnostics and healthcare industrialization.
To succeed in this role, you should have the following skills and experience
- The candidate must be Btech/M Tech/MS/Phd in computer science or electronics with research background
- Proven expertise in conducting scientific research and building proof of concept solving research problems in AI and data science
- Hands on experience with Python, C, R, Java having worked on imaging, NLP or numerical data and published publications
- Strong theoretical knowledge of Machine learning, Statistics, Mathematical.
- Hands-on experience in using and building new Image processing techniques, AI processing pipeline
- Preference for Healthcare background, Platform AI asset creation, Cloud based technologies and end to end AI pipeline creation.