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!
The Search & Recommendation Team’s mission is to accelerate our ability to return billions of hours to scientists by empowering them with the most relevant content in the most highly trafficked part of our application: the core illustrator.
As the first 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 are passionate about making ML innovations in areas such as; Ranking, Natural Language Processing, Information Retrieval, Graph Learning, Reinforcement Learning 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.
- Design and execute multi-quarter ML initiatives that deliver measurable technical, organizational, or business impacts in our Search & Recommendations domain.
- Oversee the performance and continued optimization of our search engine and recommendation systems: build machine learning models to improve query understanding, and extract user intent and context to deliver accurate, relevant, and personalized results for users.
- Prototype, optimize, and productionize ML models that help deliver key results.
- Evaluate performance of search and recommendation systems and models end to end.
- Influence the company’s ML system and data infrastructure to power personalization, recommendations to make it faster for our users to create communication materials.
- Collaborate closely with product managers, scientists, full-stack 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.
- Extensive industry experience as an ML engineer with expert level knowledge in one or more areas: Information Retrieval, Recommender Systems, Learning-to-Rank, Large Language Models, NLP, Deep Learning, Transfer Learning, Multi-task Learning, Graph Neural Network, Human-in-the-loop or similar
- Hands-on experience with with both traditional keyword-based search technologies as well as modern search paradigm utilizing vector-based retrieval algorithms and search systems such as Elasticsearch
- Experience with deep learning frameworks such as PyTorch and TensorFlow
- Experience with data exploration, analysis, and feature engineering
- 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
- Familiar with the state-of-the-art ML/AI research with publication track record
- Experience with Generative AI, Langchain, Transformer models or related
- You have experience building a variety of ML applications end to end
- Scientific and research background
BioRender has revolutionized how 1.5M+ scientists communicate their research all over the world. The app provides personalized content and creative web-based tools to our users. These powerful tools enable scientists to create beautiful visualizations easily, easy-to-read posters for conferences, and informative slide show presentations, all while giving and receiving feedback in real-time.