Senior ML Research Scientist
Rad AI- Full Time
- Senior (5 to 8 years)
Candidates should possess a Master's degree in Computer Science, Machine Learning, or a related field, with a strong preference for PhD candidates. They should have at least 7 years of experience in leading machine learning teams and projects, demonstrating a proven track record of innovation and successful product delivery. Experience with deep learning, generative models, and natural language processing is essential, along with familiarity with cloud computing platforms and large-scale data processing.
As the Head of ML at BioRender, you will lead the development and implementation of ML-powered figure generation tools, architecting systems to convert natural language descriptions into scientific figures. You will design multimodal learning systems, build generative visual models, and develop user-facing creative ML tools to enhance the scientific communication process. Additionally, you will oversee the development of ML infrastructure and contribute to the growth of BioRender’s ecosystem, ensuring scientific accuracy and visual quality are maintained throughout the process.
Online platform for creating scientific illustrations
BioRender provides an online platform for creating scientific illustrations tailored for the life sciences field. Users can access thousands of pre-drawn icons and templates covering over 30 life sciences disciplines, allowing scientists, researchers, and educators to produce professional and visually appealing figures efficiently. The platform's user-friendly interface enables clients, including academic researchers, pharmaceutical companies, and educational institutions, to create figures for research papers, presentations, and educational materials with minimal effort. BioRender operates on a subscription model, offering various plans to suit different user needs, including enterprise solutions for larger organizations. The company's goal is to simplify the process of creating high-quality scientific illustrations, making it an essential resource for effective scientific communication.