FORWARD DEPLOYED ENGINEER

About

CarbonFarm is creating a sustainable, profitable future for smallholder farmers. We believe in a future where the 1 billion land stewards in this world can live profitably while taking care of the planet. That’s why we are aligning profitability and climate impact.

Why CarbonFarm?

• Impact‑focused company helping to fight climate change
• Beautiful office spaces in Station F
• Agile team of brilliant problem solvers
• International team with 22 people, 14 nationalities
• Deep‑tech startup using modern, cloud‑based technologies

How to Apply

• A good CV is a short one (two pages good, one page better)
• No need to write a cover letter, but you can highlight something from your CV or experience
• You can send us a couple of examples that best showcase what you’ve done (e.g., links to code or projects from your studies)

Job Description

We are searching for a data scientist/engineer who can own technical scientific delivery and communication for customer missions end‑to‑end, and who can grow into a role combining operations, engineering, and product.

CarbonFarm’s work combines remote sensing data, agricultural data and machine learning. We work closely with worldwide customers to turn complex carbon projects into reliable and valuable outcomes, while feeding what we learn back into product and engineering.

As a Forward Deployed Engineer you will apply our models to each client project, adapting each time to the reality on the ground.

This role sits at the intersection of data science, engineering, and customer delivery operations. You will work closely with operations, engineering, product, and R&D to deploy and adapt CarbonFarm’s technical capabilities. That includes everything from running data pipelines and validating model outputs to shaping requirements and helping identify what should become part of the core product.

On the client‑facing front, you will work closely with our Customer Success Managers. They will manage client expectations. You will help translate client needs into technical delivery requirements and intervene in client communication when things get too technical.

This is not a consulting role. We are looking for someone who is comfortable working directly with data, code, and technical systems, and who can bridge the communication gap between a technical product and the real world in which our clients operate.

Preferred Experience

What you’ll do

• Adapt pre‑built models and data processing to the idiosyncrasies of each client project
• Collaborate with the Customer Success Manager to deliver technical results to commercial partners
• Run and maintain customer mission workflows from data intake to final output
• Work with Python, SQL, cloud systems and machine‑learning pipelines
• Validate model outputs and investigate issues in data or execution
• Support reporting and communicating the environmental outcomes for multiple customers in parallel
• Translate customer needs into actionable technical requirements
• Identify recurring delivery patterns that should be improved or productised
• Contribute to product improvements over time as delivery work reveals missing capabilities
• Leverage AI tooling to drive rapid iteration, with a strong bias for technical accuracy

What We’re Looking For

• 2 years experience in data science or in a similar technical role
• Masters degree or equivalent in engineering, computer science or similar
• Excellent communication skills, notably with regards to communicating scientific concepts to non‑technical stakeholders
• Comfortable interpreting technical results in a commercial context
• Autonomous coding in Python with 2+ years professional experience
• Ability to understand technical systems end to end, even when not every component is owned directly
• Comfortable navigating and querying SQL databases
• 1+ years experience creating or adapting data visualisations in Python or a data visualisation platform (e.g., Superset)
• Experience working with cloud platforms
• Experience working with data pipelines
• Experience applying and adjusting machine‑learning models, preferably in a professional context
• English fluency
• Paris‑based, with the ability to work in person with the team

Nice to Have

• Experience with machine‑learning pipeline operations, deployment, or monitoring
• Familiarity with workflow orchestrating tooling such as Airflow or Dagster
• Remote sensing or earth observation familiarity, notably SAR imagery
• Familiarity with GIS tools or geospatial software concepts

Additional Information

• Contract Type: Full‑Time
• Location: Paris
• Experience: > 2 years
• Occasional remote authorized