ML Engineer
Toronto, On
Confirmed live in the last 24 hours
Vevo Therapeutics

11-50 employees

In vivo drug discovery with AI
Company Overview
Vevo Therapeutics stands out in the biotechnology sector with its Mosaic platform, which is the first to scale in vivo data generation with single-cell precision, enabling the creation of an extensive atlas detailing drug interactions with patient cells. This platform's ability to conduct high-throughput in vivo experiments and generate massive datasets positions Vevo to identify novel drug targets and therapeutics that are not detectable through traditional in vitro assays. Backed by a strong seed financing round and built on licensed technology from UCSF, Vevo Therapeutics is poised to advance drug discovery by integrating patient diversity and complex biological responses into the early stages of the development process.
AI & Machine Learning
Biotechnology

Company Stage

Seed

Total Funding

$12M

Founded

2022

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

4%

1 year growth

35%

2 year growth

1050%
Locations
Toronto, ON, Canada
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Tensorflow
Keras
Pytorch
Docker
CategoriesNew
AI & Machine Learning
Requirements
  • Solid Engineering and Computer Science fundamentals
  • Experience in building, testing, training, and deploying modern neural network architectures
  • Experience with frameworks like PyTorch, Tensorflow, Keras, JAX, etc.
  • Experience and familiarity with modern software engineering practices such as VCS, Docker, CI/CD
Responsibilities
  • Support ML scientists in implementing LLM-inspired deep neural networks for single-cell transcriptomics and generative chemistry
  • Design tooling for rapid and reproducible development of ML models
  • Stay up-to-date on algorithmic developments to improve the efficiency of training large networks
Desired Qualifications
  • Experience with distributed deep learning using frameworks such as HF Accelerate, Deepspeed, and Composer
  • Practical experience with the development and testing of large language models