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.
The predicted salary is between 70000 - 90000 £ per year.
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 in York employer: Treefera
Treefera is an exceptional employer that empowers its employees to tackle complex, meaningful challenges in the climate-tech sector. With a strong focus on collaboration and innovation, team members enjoy a high-trust environment that fosters autonomy and continuous learning, alongside competitive compensation and equity options. Located remotely, Treefera offers the unique advantage of working with a diverse, cross-functional team dedicated to reshaping how nature is valued in global supply chains.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Machine Learning Scientist Remote Sensing in York
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Treefera. A friendly chat can open doors that applications alone can't. Use LinkedIn or even Twitter to connect and engage with their content.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to remote sensing. Share it during interviews or on your LinkedIn profile 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 want to see how you think and solve problems!
✨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.
We think you need these skills to ace Remote Machine Learning Scientist Remote Sensing in York
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with machine learning and geospatial Python tools in your application. We want to see how you've shipped models and tackled real-world problems, so don’t hold back on the details!
Tailor Your Application:Customise your CV and cover letter to reflect the specific requirements mentioned in the job description. We love seeing candidates who take the time to connect their experiences with what we’re looking for at Treefera.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clear communication, so make sure you explain your modelling choices and experiences without any jargon overload.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
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, it's crucial to demonstrate your ability to collaborate. Prepare examples of how you've successfully worked in cross-functional teams before, and be ready to discuss how you communicate complex ideas to both technical and non-technical stakeholders.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise. Brush up on your knowledge of model training, evaluation, and debugging. You might be asked to solve a problem on the spot or explain your thought process behind a particular modelling choice, so practice articulating your approach clearly.
✨Stay Current with Trends
Familiarise yourself with the latest trends in environmental science and machine learning, especially regarding deforestation and climate risk. Being able to discuss recent advancements or literature in the field will show your passion and commitment to staying informed, which is something Treefera values.
