As a Computer Vision Research Intern, you'll work on an R&D project involving 3D reconstruction and model training, collaborating with the AI team and mentors.
Our mission
Aquabyte is on a mission to revolutionize the sustainability and efficiency of aquaculture. It is an audacious, and incredibly rewarding mission. By making fish farming more efficient and viable, we aim to promote healthy (for the fish and environment) production of low carbon protein and mitigate one of the biggest causes of climate change. Aquaculture is the single fastest growing food-production sector in the world, and now is the time to define how technology is used to harvest the sea and preserve it for generations to come.
Aquabyte is on a mission to revolutionize the sustainability and efficiency of aquaculture. It is an audacious, and incredibly rewarding mission. By making fish farming more efficient and viable, we aim to promote healthy (for the fish and environment) production of low carbon protein and mitigate one of the biggest causes of climate change. Aquaculture is the single fastest growing food-production sector in the world, and now is the time to define how technology is used to harvest the sea and preserve it for generations to come.
We are a diverse, mission-driven team that is eager to work alongside kindred spirits. If this vision inspires you please get in touch.
Our product
We are currently focused on helping salmon farmers better understand their fish population and make environmentally sound decisions. Through custom underwater cameras, computer vision, and machine learning we are able to quantify fish weights, detect the health status, and generate optimal feeding plans in real time. Our product operates at three levels: on-site hardware for image capture, cloud pipelines for data processing, and a user-facing web application. As a result, there are hundreds of moving pieces and no shortage of fascinating challenges across all levels of the stack.
Our product
We are currently focused on helping salmon farmers better understand their fish population and make environmentally sound decisions. Through custom underwater cameras, computer vision, and machine learning we are able to quantify fish weights, detect the health status, and generate optimal feeding plans in real time. Our product operates at three levels: on-site hardware for image capture, cloud pipelines for data processing, and a user-facing web application. As a result, there are hundreds of moving pieces and no shortage of fascinating challenges across all levels of the stack.
Above all, Aquabyte is a customer-driven company. Our product development is dictated by the needs of fish farmers and we prioritize customer delight in everything we do. We are committed to building a global, collaborative team.
The role
Aquabyte’s AI team builds the computer vision and machine learning systems that observe millions of fish daily through our underwater camera fleet. We estimate fish weight via stereo 3D reconstruction, detect health conditions, and optimize feeding in real time. Our systems operate across on-site edge hardware, cloud pipelines and a customer-facing application.
The role
Aquabyte’s AI team builds the computer vision and machine learning systems that observe millions of fish daily through our underwater camera fleet. We estimate fish weight via stereo 3D reconstruction, detect health conditions, and optimize feeding in real time. Our systems operate across on-site edge hardware, cloud pipelines and a customer-facing application.
As a Research Intern, you will collaborate closely with scientists and engineers on the AI team to work on an end-to-end research project at the intersection of computer vision and aquaculture. You will have the opportunity to work in a small, experienced team with domain expertise, and have access to data, resources and mentorship to complete an impactful R&D project that involves deciding methods, designing experiments, training models, and presenting your findings. Everything we do is connected to broader company goals so by the end of your internship we want this project to be ready to be deployed so that it can have impact across farms worldwide.
In office requirements: 2 days per week minimum
Duration: 10-12 weeks
Hours: Full-time
What you'll do
- Work with your mentors to complete an end-to-end R&D Project over 10-12 weeks, from literature review through experimentation and a final deliverable.
- Work on computer vision challenges in 3D reconstruction, efficient inference, visual recognition or model robustness - applied to real production data.
- Design and run experiments, iterating with increasing depth.
- Deliver a final presentation and a clean, elegant, reproducible codebase.
- Collaborate with the wider team on translating research insights into production-ready approaches.
Minimum Qualifications
Enrolled in Masters or PhD program in computer science, electrical engineering, or a related field with a focus on Machine Learning or Computer Vision
Strong coding ability; strong grasp of Python
Have exposure to software engineering best practices (version control, testing, code reviews)
Experience with training neural networks / deep learning (ideally pytorch)
High degree of initiative; comfortable working autonomously on open-ended problems
Must return to degree program after the completion of the internship, or the internship fulfills a graduation requirement
Preferred Qualifications
- Experience with stereo vision and 3D reconstruction
- Familiarity with vision foundation models and feature extraction/matching
- Experience with efficient inference and model optimization
- Familiar with classical and deep learning based feature extraction, feature matching, and disparity estimation
- Publication record in computer vision or machine learning
At Aquabyte, we admire interesting people with a unique background. We strongly encourage you to apply even if you don’t satisfy all the requirements, and we will get back to you as soon as possible!
Top Skills
Computer Vision
Machine Learning
Python
PyTorch
Aquabyte San Francisco, California, USA Office
320 Alabama St, Unit 2, San Francisco, CA, United States, 94110
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