Principal ML Scientist

About the Role : Elucidata is looking for a Principal ML Scientist with ~4+ years of experience to join the team in Bangalore, India. This is an amazing opportunity to work in a category defining start-up company. As a Principal ML Scientist at Elucidata you'll have the opportunity to work on groundbreaking projects in life science , collaborate with an interdisciplinary team (comprising engineers, domain specialists, product managers, etc), author publications, present in conferences and contribute to the future of AI-driven technologies. Key Responsibilities : Lead and mentor a team of highly motivated ML engineers on projects that are cutting edge with an aim to publish the work done in peer reviewed journals like Nature, Science Develop and lead the implementation of strategies to align foundation models across different biological modalities - imaging, EHR, etc Aid in the ideation with product stakeholders and help the team in rapidly prototyping involving disparate data types Transform existing prototype code into optimized scalable, production-grade software Breaks down complex problems into tractable components with iterative improvements Manage the development of re-usable frameworks, models and components for future use Drive best practices in machine learning engineering and MLOps Stay up to date with latest technologies and literature recommending solutions to improve business goals Prepare research papers and contribute to conferences / webinars Qualifications : Have a desire to learn and embrace new and emerging technology / domain - life science PhD in Computer Science / Mathematics / Statistics / related STEM discipline with 4+ years of experience in a technical role, first author publications in peer reviewed journals and have managed a team of at least 3 or more ML engineers Experience working with cross-functional and distributed teams in a global and diverse environment Conversant with probabilistic models and have an understanding of the mathematical concepts underlying machine learning methods Experience integrating Machine Learning solutions into production-grade software with a sound understanding of ModelOps and MLOps principles and the ability to translate between language and methodologies used both in research and engineering fields Hands on experience with Python and one of PySpark or Scala, including demonstrable proficiency of AI / ML frameworks and tools (e.g., MLFlow, TensorFLow, PyTorch) Experience working with cross-functional and distributed teams in a global and diverse environment Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI / ML concept and results to technical and non-technical audiences.