# Machine Learning Engineer - Foundational at Harmattan AI

> Open job at Harmattan AI in Paris, France. Workplace: On-site.

Source: France Dev Jobs, https://francedevjobs.com/jobs/harmattan-ai-machine-learning-engineer-foundational-mp8276v
Posted 5 March 2026. Last checked on the employer's career site: 10 November 2026.

## Facts

- Company: [Harmattan AI](https://francedevjobs.com/companies/harmattan-ai)
- Location: Paris, France
- Workplace: On-site
- Employment type: Full-time
- French: Not required
- Skills: C++, Go, PyTorch, Rust
- Not mentioned in the job post: salary, visa sponsorship, relocation, where you can apply from

## Job description

#### 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 features.
- **Cross-Functional Collaboration:** Sync with Data Engineers on ingestion pipelines and collaborate with the Edge AI team to ensure high-performance model handoffs.**Candidate Requirements**

- **Educational Background:** A PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics.
- **Proven Experience:** Minimum of 5-6 years of experience for senior levels. Experience training and scaling deep learning vision models (ViTs, CNNs) from scratch in multi-GPU/multi-node environments. Successful application of novel SSL or multi-modal architectures (e.g., CLIP, MAE, DINO) to real-world, non-standard imaging data (IR, SAR, or hyperspectral).
- **Technical Proficiency:** Hardcore PyTorch engineering skills combined with deep mathematical intuition for representation learning. Knowledge of system-level languages (C++, Rust, or Go) and resource optimisation for edge computing.
- **Complexity & Leadership:** Ability to architect state machines for fault-tolerant data pipelines and mediate technical trade-offs between hardware and algorithm teams.
- **Commitment & Mindset:** 100% dedication to Harmattan AI’s mission of providing an ethical defence edge to allied countries. A hybrid researcher-engineer mindset that treats data quality as seriously as algorithm design

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

## How to apply

Apply on the job page, https://francedevjobs.com/jobs/harmattan-ai-machine-learning-engineer-foundational-mp8276v: its Apply button opens the employer's own application page.

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