Computer Vision Engineer

Comand AI

Paris

Sur place

EUR 100 000 - 140 000

Plein temps

14 jours+
Générateur de candidature

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Avantages offerts par ce poste

Base salary + equity

Résumé du poste

Comand AI is seeking a Computer Vision Engineer to tackle perception challenges on satellite and aerial imagery. You will own end-to-end model design, from research through production, shipping robust, real-time capable systems.

You will collaborate with data and software engineers and engage with end users to ensure models meet real-world needs and deployment constraints in field conditions.

Qualifications

  • PhD or 5–10 years of serious applied research with a track record
  • Strong deep learning expertise required
  • Experience with computer vision is highly preferred
  • Hands-on with Transformer and multimodal architectures for visual data

Responsabilités

  • Design and train architectures for object detection and segmentation on satellite imagery
  • Drive applied research agenda and track state of the art
  • Push models to production with optimized inference speed
  • Collaborate with data and software engineers to move research to production
  • Engage with end users and domain experts to define what good means

Connaissances

Deep learning
Computer vision
Python
Git
PyTorch
Transformer
Multimodal architectures
English fluency

Formation

PhD in AI, deep learning, or computer vision

Outils

PyTorch
JAX/Flax
scikit-learn
Numpy

Description du poste

Comand AI's mission is to build next-generation C2 software with real users in real deployments. We are fully indexed on the success of every single user, which means our research has to work in the field, not on a benchmark.

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
Who We're Looking For

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.

Must-have:
  • 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
What's In It For You
  • Competitive package (top 0.1% of compensation in Europe: base + equity)
  • Paris-based with occasional travel to active deployment areas
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