Senior Machine Learning Research Engineer
3 weeks ago
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. 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.
Communicate with business, data, and engineering counterparts to clarify requirements, provide feedback, and share discovered data stories with stats, charts, and formal presentations. 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
~ Experience with deep learning frameworks such as PyTorch and TensorFlow, Large Language Models, Generative AI, Langchain, Transformer models or related
~ 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
~ You have experience building a variety of ML applications end to end
~ Familiar with the state-of-the-art deep learning and AI research
~[Bonus] Familiar with the state-of-the-art ML/AI research with publication track record
You might demonstrate any of these qualifications through any mix of, for example, academic degrees, professional experience, academic research, and open source contributions. We hire talented and passionate people from a variety of backgrounds because we want our global employee base to represent the wide diversity of our customers. If you’re a builder at heart, share our company values, and are enthusiastic about making software that improves scientific communication, we want to hear from you.
We are mission-driven, and work collaboratively towards our shared vision of improving scientific communication and accelerating scientific discovery: We have a world-class NPS and a community of loyal fans. We’re remote-first and have team members across Canada and the United States. A physical office in Toronto is available, but you have the flexibility to work from anywhere.
We’re backed by top investors, accelerators, and some of the most successful life science entrepreneurs and philanthropists in the world including Y Combinator, Malala Fund founders, and Fifty Years VC.
We’re proud that women make up 2 of 3 co-founders, 53% of our team, and 37% of leadership. We are committed to building a warm, inclusive, and diverse environment. Check out our candidate resource - Engineering, Product & Design at BioRender
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