BioRender is hiring a
Machine Learning Engineer/Applied Scientist, Remote - United States, Canada

Summary

The job is for a Machine Learning Engineer/Applied Scientist at BioRender to improve the search and recommendation systems. The role requires expertise in areas such as Ranking, Natural Language Processing, Information Retrieval, Graph Learning, Reinforcement Learning, and more. The ideal candidate will have extensive industry experience, hands-on experience with deep learning frameworks, data exploration, analysis, and feature engineering, and excellent programming skills.

Requirements

• 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 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, 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

Responsibilities

• 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
• 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

Preferred Qualifications

[Bonus] Familiar with the state-of-the-art ML/AI research with publication track record

Benefits

• 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. This representation continues to grow and we are hiring!
• We are committed to building a warm, inclusive, and diverse environment