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 in Milton Keynes 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 in Milton Keynes
✨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 personal touch can make all the difference!
✨Tip Number 2
Prepare for your interviews by brushing up on your technical skills. Make sure you can confidently discuss your experience with Python, machine learning models, and remote sensing data. Practice explaining complex concepts in simple terms – it’ll impress both scientific and non-scientific folks!
✨Tip Number 3
Showcase your projects! If you've worked on any relevant machine learning models or geospatial tools, be ready to share them during interviews. Having a portfolio of your work can really set you apart from other candidates.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Treefera team. Let’s get you that job!
We think you need these skills to ace Remote Machine Learning Scientist Remote Sensing in Milton Keynes
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with machine learning and geospatial Python tools. We want to see how you've applied your skills in real-world scenarios, so don’t hold back on the details!
Tailor Your Application:Take a moment to customise your application for this role. Mention specific projects or experiences that align with our focus on remote sensing and environmental change. It shows us you’re genuinely interested!
Keep It Clear and Concise:We appreciate clear communication, so make sure your application is easy to read. Avoid jargon where possible and explain your modelling choices in a way that anyone can understand. This will help us see your thought process!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
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 geopandas, as well as your hands-on work with ML models. This will show that you’re not just familiar with the tools but can also apply them effectively.
✨Showcase Your Projects
Prepare to talk about specific projects where you've applied your machine learning skills. Highlight any models you've shipped and the impact they had. If you can, bring along examples of your code or visualisations that demonstrate your contributions. This will help the interviewers see your practical experience in action.
✨Communicate Clearly
Since you'll need to explain complex modelling choices to both scientific and non-scientific stakeholders, practice articulating your thought process. Use simple language to describe your work and be prepared to discuss uncertainties and trade-offs. This will showcase your ability to bridge the gap between technical and non-technical audiences.
✨Engage with the Team
During the interview, don’t hesitate to ask questions about the team dynamics and how they collaborate across functions. Show genuine interest in their research culture and how you can contribute to it. This will demonstrate that you’re not just looking for a job, but are keen to be part of a collaborative environment.
