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Mid LevelFull-timeRustC++Machine LearningPyTorchGoAI
Salary Range
$61,200 - $82,800 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Machine Learning Engineer to join our Foundational team in Paris. You will build the 'brain' of our tactical robots by designing and scaling large-scale, multi-modal foundational models that learn robust representations of the battlefield using Self-Supervised Learning from unlabelled Electro-Optical (EO) and Infrared (IR) data.
Key Responsibilities
- →Design neural network architectures (Vision Transformers) and loss functions (Masked Autoencoders, Contrastive Learning) to jointly learn from paired and unpaired EO and IR data
- →Manage and optimize training pipelines across multi-node GPU clusters, handling mixed-precision training and data loading
- →Develop metrics and linear-probing benchmarks to prove the latent space captures useful semantic features before distillation
- →Audit existing EO/IR data lakes and implement cross-attention mechanisms to fuse diverse sensor features
- →Collaborate with Data Engineers on ingestion pipelines and the Edge AI team for high-performance model handoffs
Requirements
- ✓PhD or highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics
- ✓Minimum of 5-6 years of experience in training and scaling deep learning vision models (ViTs, CNNs) in multi-GPU/multi-node environments
- ✓Experience applying novel SSL or multi-modal architectures to real-world, non-standard imaging data (IR, SAR, or hyperspectral)
- ✓Hardcore PyTorch engineering skills combined with deep mathematical intuition for representation learning
- ✓Knowledge of system-level languages (C++, Rust, or Go) and resource optimization for edge computing
- ✓Ability to architect state machines for fault-tolerant data pipelines and mediate technical trade-offs between hardware and algorithm teams
- ✓100% dedication to Harmattan AI’s mission of providing an ethical defense edge to allied countries
- ✓Hybrid researcher-engineer mindset that treats data quality as seriously as algorithm design
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