Machine Learning Engineer/Applied Scientist, Search & Recommendations

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 facilitate scientific discovery and understanding. We're looking for amazing people to help create the world’s go-to platform for science communication. Come join us!

The Search & Recommendation Team’s mission is to empower scientists with the most relevant content in the core illustrator of our application. As the first Machine Learning Engineer/Applied Scientist, you will partner with product, design, and engineering to build the ML and AI systems that enable 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 ML innovations in areas such as ranking, natural language processing, information retrieval, graph learning, and reinforcement learning to improve the BioRender user experience. Excitement for applied research is a must as you combine rigorous thinking with practical tooling to address modeling challenges efficiently.

You Will:

• 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, building ML models to enhance query understanding and deliver accurate, relevant, and personalized results.
• Prototype, optimize, and productionize ML models to help deliver key results and evaluate performance of systems and models end to end.
• Influence the company’s ML system and data infrastructure to enhance user communication material creation.
• Collaborate closely with product managers, scientists, full-stack engineers, and designers, proposing recommendations to maximize business impact.

Our Ideal Fit Brings:

• Extensive industry experience as an ML engineer with expertise in areas like Information Retrieval, Recommender Systems, and Learning-to-Rank.
• Hands-on experience with traditional keyword-based search technologies and modern vector-based retrieval algorithms (e.g., Elasticsearch).
• Proficiency in deep learning frameworks such as PyTorch and TensorFlow, and familiarity with Large Language Models, Generative AI, and Transformer models.
• Strong programming skills in languages such as Python, Scala, or Java and expertise in operationalizing, monitoring, and scaling ML models in cloud ecosystems.
• Experience working cross-functionally with product and engineering teams in an agile environment.
• A background in building various ML applications end to end, along with familiarity in state-of-the-art deep learning and AI research, including distributed model training and custom architectures.
• [Bonus] A publication track record in state-of-the-art ML/AI research.

We are interested in what you know, not how you learned it. You might demonstrate these qualifications through academic degrees, professional experience, research, and open-source contributions. We hire talented and passionate individuals from diverse backgrounds to represent our global customer base. If you’re excited about the role but don't meet every requirement, we still encourage you to apply. If you’re a builder at heart who shares our company values and is eager to improve scientific communication, we want to hear from you.

Why Join Us?

• We are mission-driven, working collaboratively towards a vision of improving scientific communication. BioRender figures have appeared in over 16,000 publications, and we boast a world-class NPS and a community of loyal users.
• We are remote-first with team members across Canada and the US, while also providing the option to work from our physical office in Toronto.
• Our backing comes from top investors and successful life science entrepreneurs, including Y Combinator and Malala Fund founders. Our team is diverse, with women representing 53% of our staff and 37% of our leadership.
• We are committed to building a warm, inclusive, and diverse environment and encourage you to explore our resources about working at BioRender and our interview process.