Computer Vision Engineer

As a Computer Vision Engineer, you own the hardest perception problems in the stack. The job is to crack the scientific problems that prevent us from turning multi-source sensor data (satellite, drone, ISR, OSINT) into real-time operational clarity. Your models ship into production on short cycles, used by people for whom bad output has real consequences.

In practice:

• Design and train architectures for object detection and segmentation on satellite and aerial imagery, and classification across complex image types
• Drive our applied research agenda: track the state of the art rigorously, form hypotheses, iterate fast
• Push models to production readiness: optimize for inference speed and robustness under distribution shift, which will happen in field conditions
• Work closely with data engineers and software engineers to move work from research to production without losing what matters
• Spend time with end users and domain experts to understand what “good” actually means in their context

We want scientific depth combined with the instinct to ship. Not a publication count, but evidence of both: a GitHub and Google Scholar that tell a coherent story. A recent PhD is one path in. A more experienced researcher with a strong collaborative instinct and a track record of shipping is equally welcome., * PhD in AI, deep learning, or computer vision, or 5-10 years of serious applied research with a track record to back it up

• Strong deep learning expertise, non-negotiable. Computer vision experience strongly preferred
• Solid Python, Git, and PyTorch. JAX/Flax, scikit-learn, and Numpy are real pluses
• Hands-on experience with Transformer and multimodal architectures applied to visual data
• EU citizenship (required by our defense contracts)
• English fluency
• A genuine appetite for cross-functional work: you explain your technical choices, co-design with product and operational teams, and take ownership of outcomes rather than just models

Nice to have:

• Applied work with satellite, aerial, or drone imagery
• Experience deploying models to constrained or sovereign environments
• SQL/PostgreSQL
• Prior work in defense, dual-use, or operational tech
• Geospatial data processing background

• Competitive package (top 0.1% of compensation in Europe: base + equity)
• Paris-based with occasional travel to active deployment areas

AI-powered command for modern defence.

At Comand AI, we build the command software modern forces need. AI-native from day one and designed to work with what forces already use.

Prevail reads mission data and terrain, surfaces predicted threats, and hands forces real-time courses of action while feeding lessons learned back into doctrine. It turns data overload into a decision advantage instead of a liability.

The team brings together engineers who’ve shipped at Palantir and OpenAI. Prevail is built for people who can’t afford to lose.

We raised a €32 million Series A to scale the mission.