Machine Learning Engineer - Foundational

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About this role

Machine Learning Engineer - Foundational Paris, Île-de-France, France 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 As a Machine Learning Engineer on our Foundational team in Paris, you will build the "brain" of our tactical robots. You will design and scale large-scale, multi-modal foundational models that learn robust representations of the battlefield using Self-Supervised Learning (SSL) from massive amounts of unlabelled Electro-Optical (EO) and Infrared (IR) data. Your work provides the critical foundational weights that our Edge AI team distills into hyper-accurate models running on tactical hardware. Responsibilities - Multi-Modal SSL Architecture Design: Design neural network architectures (Vision Transformers) and loss functions (Masked Autoencoders, Contrastive Learning) to jointly learn from paired and unpaired EO and IR data. - Distributed Training Infrastructure: Manage and optimise training pipelines across multi-node GPU clusters, handling mixed-precision training and data loading. - Representation Evaluation: Develop metrics and linear-probing benchmarks to prove the latent space captures useful semantic features before distillation. - Data Strategy: Audit existing EO/IR data lakes and implement cross-attention mechanisms to fuse diverse sensor

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