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- Tasks: Develop and scale innovative backend systems for sustainable agriculture using cutting-edge tech.
- Company: Mission-driven startup focused on climate resilience and food security.
- Benefits: Competitive salary, equity options, and major career growth opportunities.
- Why this job: Make a real impact on sustainable farming while working with advanced satellite and ML technologies.
- Qualifications: Strong Python skills, AWS experience, and familiarity with data pipelines and ML workflows.
- Other info: Join a diverse team that values experimentation and offers a dynamic work environment.
The predicted salary is between 36000 - 60000 £ per year.
This is a unique opportunity to join a mission-driven startup applying cutting-edge data engineering, satellite science, and backend development to help farmers grow more sustainably and profitably. You’ll work at the intersection of satellite imagery, backend systems, and machine-learning infrastructure, helping to build and scale a groundbreaking agricultural intelligence platform.
What you’ll be doing
- You will own and contribute to backend and ML infrastructure across a wide range of technical areas, including:
- Migrating our machine-learning training pipelines to AWS (currently running largely locally)
- Designing and implementing ML testing pipelines, including visualisation tools to assess model performance
- Building tooling to analyse spectral signals at specific parts of imagery, enabling better diagnosis of where and why models perform well or poorly
- Supporting atmospheric correction testing pipelines and contributing to visualisation tools used to validate results
- Integrating with new satellite imagery feeds and partnering APIs (including tractor/precision agriculture data)
- Developing and maintaining data pipelines for ML workflows and crop-growth modelling
- Enhancing geo-rectification workflows and improving performance of atmospheric correction systems
- Collaborating closely with engineering, data science, and product teams to turn insights into production-ready features
- Contributing to both R&D-heavy and commercially driven engineering initiatives
What you can bring
- Strong Python skills, including experience with data processing libraries (e.g. Numpy, Pandas). Bonus: RasterIO or other geospatial tooling experience.
- Experience with AWS and containerised environments (Docker).
- Familiarity with backend frameworks (FastAPI, Flask, or Django).
- Experience working with data pipelines, ML workflows, or MLOps-style environments.
- Ideally some experience with TypeScript for visualisation or frontend-adjacent tooling.
- Comfort navigating ambiguity, proposing improvements, and balancing short-term execution with long-term architecture.
- Strong communication skills: able to document, explain, and align with technical and non-technical stakeholders.
- Prior experience in a fast-paced or startup environment is beneficial.
What’s in it for you
- A rare engineering role that bridges backend systems, satellite technology, and machine-learning infrastructure.
- The chance to build tools at the cutting edge of geospatial and spectral analysis.
- Work with a smart, ambitious team that values experimentation and delivery.
- Meaningful equity at an exciting inflection point of company growth.
- Major career growth opportunities as the company scales.
- A real chance to shape technology that impacts climate resilience, food security, and sustainable agriculture.
We believe diverse teams build better products and insights. We welcome applications from individuals of all backgrounds and experiences and are committed to fostering an inclusive workplace where everyone can thrive.
Full Stack Engineer employer: Mirai Talent
Contact Detail:
Mirai Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Full Stack Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to backend systems or machine learning. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s mission. Be ready to discuss how your experience with Python, AWS, and data pipelines can contribute to their goals in sustainable agriculture.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission-driven team.
We think you need these skills to ace Full Stack Engineer
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for sustainable agriculture and technology shine through. We want to see how your values align with our mission at StudySmarter!
Tailor Your Experience: Make sure to highlight your relevant skills and experiences that match the job description. Whether it's your Python prowess or AWS experience, we want to know how you can contribute to our team.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your past projects and achievements, so we can easily see how you fit into our vision.
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 get the ball rolling on your journey with StudySmarter.
How to prepare for a job interview at Mirai Talent
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and AWS. Brush up on your knowledge of data processing libraries like Numpy and Pandas, and be ready to discuss how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles, particularly around backend systems or machine learning workflows. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your ability to navigate ambiguity.
✨Demonstrate Collaboration
Since this role involves working closely with various teams, be ready to share examples of how you've successfully collaborated with both technical and non-technical stakeholders. Highlight your communication skills and how you’ve aligned project goals across different departments.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the company’s mission and the role. Inquire about their current projects involving satellite imagery and machine learning, or ask how they envision the future of sustainable agriculture technology. This shows you’re not just interested in the job, but also in contributing to their vision.
