ML Researcher (Agriculture) - REMOTE
🌎 100% Remotely with flexible hours
💵 6 600 - 10 000 USD per month depending on the experience
☑️ B2B, long-term permanent contract signed directly with the client
🌴 Unlimited paid time off
💻 The international insurance company that protects farmers and people from catastrophic weather conditions
Looking to make an impact and grow within a leading organization? Do you want your input to be heard and taken into consideration? Apply and create a digital future with us!
As a Machine Learning Researcher, your day-to-day will be focused on creating higher-level data products based on remote sensing data. You will communicate with the engineering team to turn the algorithms into production-quality services and participate in the process of implementation, so you will get ample opportunity to learn new skills.
In addition, you will be a go-to expert on existing datasets with the possibility of creating ad hoc analyses.
- Great knowledge of Python
- Independent data analysis and signal processing skills to prototype new and existing algorithms
- Prior software development experience (agile development, git, rapid prototyping)
- Experience with satellite radar (active/passive) and/or multi/hyper-spectral imagery
- Masters but preferably Ph.D. science degree in computer sciences, remote sensing, machine learning signal processing, etc.
Nice to have:
- Previous experience with big data is an advantage
- Knowledge of modern cloud deployment tools (AWS, Docker, Kubernetes, etc)
- Prototype and implement algorithm related to radar, multi/hyper spectral imagery
- Create statistical models for time-series processing and data fusion algorithms
- Rapid algorithm prototyping in Python
- Participate in geospatial artificial intelligence model development (supervised and unsupervised)
What do we offer?
- 100% remotely
- In case needed, well-located office space in Prague
- Unlimited PTO
- Remote setup lump sum
- Health insurance benefit
Referral bonus: 5,000 PLN if we hire an engineer based on your recommendation