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 in order to accelerate scientific discovery and understanding. We're looking for amazing people to help create the world's go-to-place and platform where science is communicated. Come join us!

This AI figure generation team's mission is to accelerate our ability to return billions of hours to scientists by empowering them with tools for faster figure creation in the most highly trafficked part of our application: the core illustrator.

As one of the founding Machine Learning Engineer/Applied Scientist, you will partner with product, design, and engineering to build the ML and AI system that enables scientists to effortlessly create beautiful and effective figures. We are looking for individuals at senior and staff levels who are product-driven and passionate about making AI innovations in areas such as; Object Detection, Natural Language Processing, Computer Vision, Multi-Modal Models, Generative Models and Image Processing to help improve the BioRender user experience! Excitement for applied research is a must as you combine rigorous thinking with practical tooling to meet these modeling challenges efficiently.

You will:

• Design and execute multi-quarter AI/ML initiatives that deliver measurable technical, organizational, or business impacts in our Figure generation domain.
• Oversee the performance and continued optimization of the figure generation model system: build machine learning models to improve design understanding, and extract user intent and context to deliver accurate, relevant, and personalized figures for users.
• Prototype, optimize, and productionize ML models that help deliver key results.
• Evaluate performance of figure generation systems and models end to end.
• Influence the company's ML system and data infrastructure to power figure creation to make it faster for our users to create communication materials.
• Collaborate with product managers, scientists, full-stack and platform engineers, and designers on product teams.
• Communicate with business, data, and engineering counterparts to clarify requirements, provide feedback, and share discovered data stories with stats, charts, and formal presentations. Propose recommendations to maximize business impact.

Our ideal fit brings:

• Extensive industry experience as an ML engineer with expert level knowledge in one or more areas: Object Detection and Image Segmentation, Computer Vision, Deep Learning, Transfer Learning, VLM, Multi-Modal or Generative model or similar.
• Hands-on experience with deep learning frameworks such as PyTorch and TensorFlow.
• Experience with distributed model training
• Experience developing custom model architectures.
• Excellent programming skills with one or more of the following languages: python, scala, java.
• Expertise with operationalizing, monitoring, and scaling machine learning models and pipelines in cloud ecosystems.
• Previous experience working cross-functionally with product and engineers to deliver solutions with complex requirements in an agile environment.

Nice to haves:

• Familiar with the state-of-the-art ML/AI research with publication track record
• Experience with Generative AI, Transformer models or related
• You have experience building a variety of ML applications end to end
• Scientific and research background