Machine Learning Engineer
Description For Machine Learning Engineer
BioRender is revolutionizing scientific communication by creating a platform that helps scientists create beautiful, accurate biological figures. As a Machine Learning Engineer, you'll join a mission-driven company that's already impacting scientific discovery, with their figures appearing in over 16,000 publications.
The role combines cutting-edge machine learning with scientific visualization, focusing on developing systems that can translate complex biological concepts into clear, accurate visuals. You'll work on challenging problems that go beyond standard ML solutions, including computer vision, code generation, and natural language processing for figure editing.
The ideal candidate brings deep ML expertise and a passion for scientific communication. You'll need extensive experience with modern ML frameworks, distributed training, and custom model architectures. The role offers a unique opportunity to work at the intersection of AI and scientific visualization, with direct impact on how research is communicated globally.
BioRender offers a remote-first environment with a physical office in Toronto, competitive compensation ($200K-$300K), and the chance to work with a diverse team where 53% are women, including two of three co-founders. The company is backed by prestigious investors including Y Combinator and shows strong profitability and growth.
This is an opportunity to join a successful, mission-driven company that's making scientific communication more accessible and efficient. You'll work with a collaborative team, have the flexibility to work remotely, and contribute to accelerating scientific discovery through better visual communication tools. The role combines technical challenges with meaningful impact, making it ideal for an experienced ML engineer who wants to make a difference in scientific research and communication.
Responsibilities For Machine Learning Engineer
- Design and execute multi-quarter AI/ML initiatives
- Oversee performance and optimization of figure generation model system
- Prototype, optimize, and productionize ML models
- Evaluate performance of figure generation systems
- Influence ML system and data infrastructure
- Collaborate with product managers, scientists, and engineers
- Communicate with business and engineering counterparts
- Combine computer vision and code generation
- Create story-driven scientific visuals
- Enable chat-driven figure editing
Requirements For Machine Learning Engineer
- Deep technical expertise in machine learning
- Extensive industry experience as an ML engineer
- Expert level knowledge in Object Detection, Image Segmentation, Computer Vision, Deep Learning, Transfer Learning, VLM, or Multi-Modal models
- Experience with PyTorch and TensorFlow
- Experience with distributed model training
- Experience developing custom model architectures
- Excellent programming skills in Python, Scala, or Java
- Expertise with operationalizing ML models in cloud ecosystems
- Experience working cross-functionally in agile environment
Benefits For Machine Learning Engineer
- Remote-first work environment
- Physical office in Toronto available
- Inclusive and diverse workplace
- Work with top investors and accelerators
- Mission-driven company
- Strong company growth and profitability
- Flexible work location
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