[Hiring] Founding Computer Vision Engineer @Retide Labs

Role Description

We're looking for a 'Founding Computer Vision & Perception Engineer' to lead the development of Retide's aerial perception capabilities. You'll work at the intersection of computer vision, machine learning, robotics, and environmental sensing to explore how AI can transform aerial data into useful intelligence about plastic pollution.

You'll take ownership of Retide's computer vision and perception work, building on what we've developed so far and helping shape where it goes next. You'll work with real-world data, develop and test models, and take them into the field to understand how they perform outside the lab. You'll have significant influence over Retide's AI architecture, datasets, and technical direction.

What You'll Work On

• Building initial detection and segmentation models from our existing drone and beach imagery datasets.
• Traveling to Brazil, west-coast Canada, or Southeast Asia for at least one field deployment, working directly alongside cleanup partners.
• Helping us decide where to build custom architectures versus adapt existing ones — especially for small-object detection in complex, cluttered environments.

Beyond that, the role spans the full perception stack: multimodal sensor fusion, real-time and edge AI, model uncertainty and human-in-the-loop systems, and active learning as our datasets grow. You'll work closely with our robotics and software team to treat perception as part of an entire sensing system, not just a model trained on a static dataset.

Qualifications

• Strong experience in computer vision, machine learning, robotics perception, or a closely related field.
• Built and evaluated real-world perception systems.
• Experience with object detection, segmentation, and modern deep learning approaches.
• Comfortable working with imperfect and evolving datasets.
• Ability to move from research to prototype to experiment to iteration quickly.
• Takes ownership rather than waiting for detailed requirements.
• Excited to spend time in the field, not just behind a computer.

Requirements

• Experience with PyTorch, aerial imagery, small-object detection, edge AI, active learning, uncertainty estimation, sensor fusion, remote sensing, multimodal imaging, or robotics is valuable.
• More interested in what you can build and how quickly you can learn than whether you check every box.

Commitment & Compensation

We're flexible on commitment level. This role can start at 20 hours per week or move to full-time immediately for the right person — we'd rather structure around what works for you than force a fixed schedule this early.

At our current pre-seed stage, this is an equity-based role, with the intention of transitioning to salary + equity following our next funding round, currently targeted for Q2 2027.

Location & Field Work

Retide is remote worldwide — you can be based anywhere. Our founder is a digital nomad. This role involves frequent international travel for field testing and deployments, concentrated across Canada, Brazil, and Southeast Asia.

Core travel costs for scheduled field deployments are covered by Retide. This isn't a purely remote AI role. We want someone excited to take models into the field, work alongside our partners, see where they fail, and use that to make them better.

What It's Like to Build at Retide

We're small, ambitious, and still early. That means everyone has a voice in what Retide becomes. We value curiosity over ego, ownership over titles, and progress over perfection. We care about rigorous science and thoughtful engineering, but we also believe technology only matters if it works outside the lab — which means learning alongside the communities and organizations already doing this work on the ground.

You should be excited by ambiguity, comfortable challenging assumptions, and willing to get your hands dirty — sometimes literally.

Why Join Now

You'll join Retide at a point where many of our most important technical decisions have yet to be made. You'll have the opportunity to shape our perception architecture, datasets, research direction, and engineering culture from the beginning — working directly with the founder and a small technical team, with significant ownership over what you build.

The models you develop won't live only in a benchmark or research paper. They'll go into the field and help us build a better way to understand plastic pollution in the environments where it actually exists.

If you're excited about computer vision, robotics, oceans, and applying AI to one of the world's most visible environmental problems, we'd love to hear from you.