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Full-Time

Machine Learning Engineer/Applied Scientist

Search & Recommendations

Confirmed live in the last 24 hours

Biorender

Biorender

201-500 employees

Online platform for creating scientific illustrations

Hardware
Energy
Enterprise Software
Design
Biotechnology

Senior, Expert

Remote in USA + 1 more

Category
Applied Machine Learning
Deep Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Agile
Python
Tensorflow
Data Structures & Algorithms
Pytorch
Java
Elasticsearch
Scala
Natural Language Processing (NLP)
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
  • Familiar with the state-of-the-art deep learning and AI research
  • Experience with distributed model training
  • Experience developing custom model architectures
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: 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.

BioRender provides an online platform for creating scientific illustrations tailored for the life sciences sector. Users can access thousands of pre-drawn icons and templates across more than 30 life sciences fields, allowing scientists, researchers, and educators to produce professional and visually appealing figures efficiently. The platform's user-friendly interface and extensive library help reduce the time and effort needed to create high-quality illustrations for research papers, presentations, and educational materials. BioRender differentiates itself from competitors by focusing specifically on the life sciences and offering a subscription-based model with various plans, including options for larger organizations. The goal of BioRender is to simplify the process of scientific communication by enabling users to create accurate and engaging figures with ease.

Company Stage

Seed

Total Funding

$17.2M

Headquarters

Toronto, Canada

Founded

2017

Growth & Insights
Headcount

6 month growth

9%

1 year growth

21%

2 year growth

87%
Simplify Jobs

Simplify's Take

What believers are saying

  • BioRender's platform significantly reduces the time and effort required to create professional scientific illustrations, enhancing productivity for researchers and educators.
  • The company's focus on life sciences and its comprehensive resources make it a valuable tool for a wide range of clients, from academic institutions to biotech firms.
  • BioRender's innovative approach and continuous updates, such as the Graphical Abstract Contest, demonstrate its commitment to supporting the scientific community.

What critics are saying

  • The niche focus on life sciences may limit BioRender's market potential compared to more versatile illustration tools.
  • Dependence on subscription revenue means that fluctuations in user retention and acquisition could impact financial stability.

What makes Biorender unique

  • BioRender's platform offers a vast library of pre-drawn icons and templates specifically tailored for the life sciences, setting it apart from generic illustration tools.
  • The user-friendly interface and focus on scientific accuracy make it an indispensable tool for researchers and educators who need to produce high-quality figures quickly.
  • BioRender's subscription-based model with various plans caters to different user needs, from individual researchers to large organizations, providing flexibility and scalability.