Vivid Machines™ develops computer vision and machine learning technology to improve yield and product quality in fruit production. We help predict and manage yield by providing a clear view of tree-level data in real time. We also help diagnose pests, disease, and nutrient deficiencies through our vision system which is able to see early indications that would be invisible to the human eye.
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We build smart technology to help fruit farmers optimize quality and yield.
Full company description
Vivid Machines™ develops computer vision and machine learning technology to improve yield and product quality in fruit production.
We help predict and manage yield by providing a clear view of tree-level data in real time. We also help diagnose pests, disease, and nutrient deficiencies through our vision system which is able to see early indications that would be invisible to the human eye.
LinkedIn followers
2,841
People associated on LinkedIn
23
Reported office locations
Toronto, ON, CA
Business categories
AgTech
Artificial Intelligence
Artificial Intelligence (AI)
Machine Learning
Software
Other recorded names
Vivid Machines
Specialties
Artificial Intelligence
SaaS Software
Sensors
Industrial Design
and Machine Learning
Profile identifies a recruitment agency
No
Reported total investment
4,737,046
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Vivid Machines: Vivid Machines™ develops computer vision and machine learning technology to improve yield and product quality in fruit production.
Candidates need several years building and running production front-end and back-end applications, with strong TypeScript and Python. They need data modelling and live-schema migration experience, AWS serverless experience, and secure API and access-control design. Rust, React and geospatial experience are nice to have.
Rust, TypeScript, Python, Prisma, AWS Lambda, AWS API Gateway
Vivid Machines: Vivid Machines™ develops computer vision and machine learning technology to improve yield and product quality in fruit production.
3+ YOECandidates need 3 to 5 years of QA testing experience, hands-on manual testing across at least two of web, mobile or backend systems, and working knowledge of Python with pytest. Familiarity with Jira or TestRail, CI/CD concepts and clear written documentation is also needed.
Vivid Machines: Vivid Machines™ develops computer vision and machine learning technology to improve yield and product quality in fruit production.
Candidates need strong systems programming in C, C++ or Rust and experience with real-time streaming or vision pipelines. Hands-on work deploying vision models to edge devices, low-level camera and sensor experience, and Linux embedded skills are also required, along with self-direction in a small team.