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Computer Vision Engineer
David Mensah
Full-time · Mid-level · Lisbon
About the role
I started this company three years ago in my spare bedroom with a camera, a used GPU, and a single client: a small vineyard in Portugal that wanted to detect early-stage disease on grape leaves before it spread. That client is now one of 40 farms across four countries running our crop health monitoring system. We process roughly 2 million images per week. The model pipeline I built alone in year one is now maintained by a team of three — but we need a fourth. Someone who thinks carefully about the gap between a model that performs well on a validation set and one that holds up in a field at 7am with dew on the lens and patchy cloud cover changing the light every thirty seconds. If you've worked on computer vision systems in messy real-world conditions — agriculture, manufacturing, outdoor environments — I want to hear from you. This isn't a job with a lot of ceremony. We build, we test in the field, we fix what's broken, and we ship again.
Responsibilities
- Extend and improve the crop disease detection models for two new crop types in Q3
- Design data augmentation strategies for environmental variability (lighting, weather, sensor drift)
- Help build an automated labelling and annotation workflow to reduce manual annotation time
- Test models in real field conditions and diagnose failure modes with domain experts
- Document model architecture decisions, training configs, and evaluation benchmarks
Requirements
- 3–5 years of computer vision engineering with at least one production deployment in a real-world environment
- Strong PyTorch — you implement, train, and debug models yourself, not just run inference on pre-trained weights
- Solid understanding of object detection and image classification across varied conditions
- NumPy and OpenCV for image processing and augmentation pipelines
- Familiarity with model deployment on edge hardware or constrained environments
- Exposure to agricultural or environmental imaging is a genuine bonus — but enthusiasm and rigour matter more
Benefits
- Work with tangible, visible real-world impact on sustainable agriculture
- Full remote with optional quarterly visits to field trial sites (flights covered)
- $88,000 – $112,000 base salary + profit share
- $1,500 equipment budget on joining
- Small, flat team — your opinions shape the direction
Job Type
Full-time
Level
Mid-level
Language
English
Salary Range
$88,000 – $112,000
AI Expertise
AI & Machine Learning Engineers
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