ML Engineer

• Location: Paris (75017), France – Hybrid
• Reports to: Head of Data
• Contract: Full Time
• Start: ASAP
• Experience: 2+ years (Junior / Mid)

‍

As a Machine Learning Engineer (Computer Vision), you will be responsible for the training, optimization, deployment, and monitoring of deep learning models across our ISR & Counter-UAS product line.

You will work on the full ML lifecycle, from dataset curation to running optimized inference models on edge compute units (Jetson & RPI) or cloud based GPU.

This role is hands-on, technical, and impactful: your work will directly influence field performance.

You will:

• Improve and maintain training pipelines for detection, segmentation, and tracking models.
• Define and automate evaluation frameworks.
• Drive dataset governance: versioning, triage, augmentation, synthetic data, annotation workflows.
• Optimize models for edge inference (weights conversion, quantization, pruning).
• Contribute to deployment workflows and system integration with embedded & onboard compute.
• Implement monitoring & feedback loops to ensure reliability in real operational conditions.
• Work closely with Software, Hardware, and Field Ops teams to iterate quickly from lab → field → deployment

You have already shipped computer vision models into real usage and you know how to own an ML pipeline end-to-end.

• 2+ years of experience as ML Engineer / Computer Vision Engineer.
• Strong skills in Python and deep learning frameworks (PyTorch preferred).
• Hands-on experience training and evaluating models on large-scale image/video datasets (detection, segmentation, multi-object tracking).
• Proven usage of experiment tracking and dataset/version governance (ClearML / MLflow / W&B + DVC or equivalent).
• Operates comfortably with MLOps fundamentals: Docker, Git best practices, reproducible pipelines, CI/CD.
• Able to take ownership, propose improvements, write clear documentation, and deliver production-level code, not research-only prototypes.

‍

• Deployment experience on edge computing hardware (Jetson / RPI), including TensorRT / ONNX Runtime / quantization workflows.
• Understanding of real-time performance constraints (latency budgets, throughput optimization, memory constraints, thermal/power envelopes).
• Experience working in or alongside robotics, defense systems, aerospace, or dual-use applications, where reliability > benchmark scores.

‍

European & Technolo-gical sovereignty

Rigor & Audacity

Pragmatic, Field-Oriented Innovation

Resilience in Extreme Conditions

• Opportunity to work on real-world ISR & Counter-UAS computer vision projects.
• End-to-end exposure to the ML lifecycle: from dataset preparation to deployment on embedded systems.
• A highly collaborative and multidisciplinary environment with AI, defense, and robotics experts.
• A hybrid and flexible working setup in the heart of Paris.

‍