Machine Learning Engineer (Semantic Scene Understanding)

About US

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.

Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.

About the Role

We are looking for a Machine Learning Engineer to join our Semantic Scene Understanding team in Paris. In this role, you will design the core algorithms to extract semantic information in real-time from the theatre of operations as seen through the different cameras of our different UAVs, to improve the operator’s scene understanding.

Responsibilities

• Design and Train: Develop state-of-the-art machine learning algorithms for semantic segmentation, object detection, and classification tailored to aerial imagery.

• Advanced Feature Extraction: Build high-level tactical features on top of base semantic data, such as real-time road vectorization, trafficability analysis, and dynamic obstacle mapping.

• Multi-Agent Fusion: Architect pipelines that temporally and spatially align semantic data from multiple moving UAVs into a cohesive Common Operational Picture (COP).

• Edge Optimization: Optimize and deploy these algorithms directly into our tactical C2 platform, utilizing quantization, pruning, and hardware acceleration to meet strict real-time compute constraints.

• Candidate Requirements

• Educational Background: MSc in Computer Science, Machine Learning, or a related field. A PhD is a strong plus.

• Foundational Knowledge: Deep understanding of Machine Learning theory, Linear Algebra, and 3D-Geometry algorithms.

• Core Tech Stack: Expert-level command of Python and deep learning frameworks (PyTorch).

• Performance Engineering: Experience with C++ and inference optimization frameworks (e.g., TensorRT, ONNX Runtime, CUDA) is highly desirable.

• Domain Experience (Plus): A track record of shipping CV/ML algorithms in production, particularly for edge/embedded systems or involving aerial (EO/IR) imagery.

• Strong Ownership: Ability to take a feature from an ArXiv paper all the way to a ruggedized tactical PC.

• Adaptability & Mission Focus: Thrives in a fast-paced startup environment and is 100% dedicated to building ethical defense technologies that bring a strategic edge to allied nations.

• Communication: Excellent verbal and written communication skills to collaborate effectively with software engineers and hardware teams.

• We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.