ML Engineer
| department | engineering / machine-learning |
|---|---|
| Equity (shares) | 10000 |
| Level | 🥈Middle |
| Ongoing equity (%) | 1 |
| Person |  Fam A. Shihata, Jassem Manita |
| Responsibilities | - need to optimize models. Better precision, less memory usage - gather and improve training datasets - need to integrate new vision models - need to run it on edge devices - build own GPU inference server |
| company phase | 0-angel |
Position ad
Gratheon is a technology company based in Tallinn, Estonia that focuses on helping beekeepers organise and automate their apiaries. We develop web application that integrates with IoT devices to provide real-time metrics for beekeeping operations. Our use of machine learning allows us to identify and alert beekeepers of potential dangers. As part of our long-term vision, we aim to automate this process with robots. Our code is open source and processes are transparent.
Role Description
This is a volunteer remote role for a Machine Learning Engineer at Gratheon. As a Machine Learning Engineer, your main responsibilities will include developing and implementing machine learning models for bee detection and danger alert systems. You will also collaborate with the team to optimize the performance of the web application and integrate new technologies. This role requires strong expertise in pattern recognition, computer science, neural networks, statistics, and algorithms.
Qualifications
- Background in computer science or statistics
- Experience working with machine learning frameworks and libraries (Pytorch, Tensorflow)
- Experience in preparing and curating datasets
- Proficiency in programming languages such as Python
- Expertise in developing and implementing neural network models (Yolo, U-net, Transformer-based) and workflows
Also nice to have:
- Beekeeping experience
- Video processing experience (python, ffmpeg, gstreamer)
- Ability to work independently and remotely
- Values ecosystem sustainability and environmental restoration
As a volunteer, you will not receive any monetary compensation (until we get pre-seed round investments). This is an opportunity to join a company at very early phase, learn things, have fun in the process and be part of the open-source community.