Staff Machine Learning Engineer/Applied Scientist - AI Figure Generation

At BioRender, our mission is to accelerate the world's ability to learn, discover and communicate science. We are passionate about democratizing science communication to accelerate scientific discovery and understanding. As a Staff Machine Learning Engineer/Applied Scientist, you'll be part of the founding AI figure generation team.

The role focuses on building ML and AI systems that enable scientists to effortlessly create beautiful and effective figures. You'll work at the intersection of Object Detection, Natural Language Processing, Computer Vision, Multi-Modal Models, and Generative Models to enhance the BioRender user experience.

Key Responsibilities:

• Lead the design and execution of AI/ML initiatives that deliver measurable impact
• Build and optimize machine learning models for figure generation and design understanding
• Extract user intent and context to deliver personalized figures
• Prototype and productionize ML models
• Evaluate and optimize system performance end-to-end
• Shape the company's ML infrastructure
• Collaborate across functions with product, design, and engineering teams

Technical Requirements:

• Expert knowledge in computer vision, deep learning, and ML systems
• Hands-on experience with PyTorch and TensorFlow
• Distributed model training expertise
• Custom model architecture development
• Strong programming skills in Python, Scala, or Java
• Experience with ML operations and scaling
• Track record of cross-functional collaboration

Nice to Have:

• Research publication track record
• Experience with Generative AI and Transformer models
• End-to-end ML application development
• Scientific background

BioRender offers a unique opportunity to work on cutting-edge AI applications in scientific visualization. You'll be part of a team returning billions of hours to scientists by making figure creation faster and more efficient. The role combines applied research with practical implementation, requiring both rigorous thinking and pragmatic engineering approaches.

Join us in democratizing science communication and accelerating scientific discovery. You'll work with a talented team of 205+ people, backed by Y Combinator (W18 batch), and help shape the future of scientific visualization tools.