At a Glance
- Tasks: Develop and deploy machine learning models for remote sensing applications.
- Company: Join Treefera, a pioneering first-mile intelligence platform in agri-tech.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on research and innovation.
- Why this job: Make a real impact on global agriculture with cutting-edge technology.
- Qualifications: Degree in a quantitative field and 3+ years of machine learning experience.
Grow with Treefera. We are a first-mile intelligence platform, delivering granular visibility into the point of origin in global ag produce QA artefacts (maps, plots, model cards, error analyses) that internal teams and clients can trust and defend. Partner with Engineering to take models into scalable, reproducible inference pipelines across millions of plots, and contribute to a strong research culture across Science, AI and Engineering - reviewed code, shared tooling, and active engagement with EO/ML literature.
Who you are:
- Must-have requirements:
- Degree in a quantitative field: environmental/earth science, computer science, physics, maths, engineering, or similar.
- 3+ years of applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models.
- Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem.
- Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision transformers) using PyTorch, as well as classical methods (gradient boosting, random forests) with scikit-learn.
- Demonstrable experience with remote sensing data (optical, SAR) and an understanding of the sensor-specific quirks that matter for modelling.
- Comfortable with Git, cloud compute (AWS or similar), and collaborative codebases.
- Clear written and verbal communication: can explain modelling choices, uncertainties, and trade-offs to scientific and non-scientific stakeholders.
- Domain exposure: deforestation, land-use change, biomass/canopy-height estimation, climate risk, or supply-chain transparency.
- Desirable requirements:
- Experience using EO foundation models as a downstream substrate - building lightweight classifiers, regressors, or similarity-search workflows on top of frozen embeddings (e.g., AlphaEarth Foundations, Clay, etc).
- Comfortable fine-tuning or pretraining where the case justifies it.
- Multi-modal fusion experience - combining optical (Sentinel-2, Landsat), SAR (Sentinel-1, PALSAR), and/or LiDAR (GEDI, ICESat-2) into unified predictions.
- Time-series modelling for environmental change detection - temporal transformers, sequence models, or self-supervised approaches.
- Comfortable building with AI-assisted development tools as a core part of your workflow.
- Familiarity with Google Earth Engine, Microsoft Planetary Computer, AWS Open Data, or other STAC-based catalogues.
- Experience working in cross-functional teams working alongside solutions architects, sales, and engineering.
Who you’ll work with:
You’ll report to the Science Team Lead and partner day-to-day with the wider Science Team while working closely with Engineering and Product teams.
Interview process
Remote Machine Learning Scientist Remote Sensing employer: Treefera
At Treefera, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to grow and excel in their careers. As a Remote Machine Learning Scientist, you will have the unique opportunity to contribute to impactful projects in environmental science while working alongside a passionate team dedicated to advancing research in AI and remote sensing. With a strong emphasis on professional development and a commitment to sustainability, Treefera offers a rewarding environment where your expertise can make a real difference.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Machine Learning Scientist Remote Sensing
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Treefera. Use LinkedIn or even Twitter to connect with current employees and ask about their experiences. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to remote sensing. Share your GitHub link during interviews or networking events to give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. Practice coding challenges and be ready to discuss your past projects in detail. We recommend using platforms like StudySmarter to refine your knowledge and boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Treefera team. Let’s get you that dream job!
We think you need these skills to ace Remote Machine Learning Scientist Remote Sensing
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in machine learning and remote sensing. Use keywords from the job description to show that you’re a perfect fit for the role. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for machine learning and how it relates to our mission at Treefera. Don’t forget to mention specific projects or experiences that demonstrate your expertise in geospatial Python tooling.
Showcase Your Projects:If you’ve worked on relevant projects, make sure to include them in your application. Whether it’s a GitHub repo or a portfolio, we love seeing practical examples of your work, especially those involving remote sensing data and ML models.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at Treefera!
How to prepare for a job interview at Treefera
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially those related to remote sensing and geospatial data. Be ready to discuss your experience with Python libraries like rasterio and PyTorch, as well as any specific projects you've worked on that relate to the job description.
✨Showcase Your Collaboration Skills
Since you'll be working closely with Engineering and Product teams, highlight your experience in cross-functional teams. Prepare examples of how you've effectively communicated complex modelling choices to both technical and non-technical stakeholders.
✨Prepare for Technical Questions
Expect to dive deep into your technical expertise during the interview. Brush up on your knowledge of model training, evaluation, and debugging. Be ready to explain your approach to using classical methods and deep learning techniques, and how you've applied them in real-world scenarios.
✨Demonstrate Your Passion for Research
Treefera values a strong research culture, so come prepared to discuss recent literature in EO/ML that excites you. Share how you stay updated with industry trends and how you’ve applied new findings to your work, showing your commitment to continuous learning.
