Machine Learning Engineer - Foundational

The role

You will design and scale large-scale, multi-modal foundational models to learn representations of the battlefield. This work involves using Self-Supervised Learning from unlabelled Electro-Optical and Infrared data.

What you will do

• Design neural network architectures and loss functions to learn from paired and unpaired EO and IR data.
• Manage and optimise training pipelines across multi-node GPU clusters.
• Develop metrics and linear-probing benchmarks to prove latent space captures useful semantic features.
• Audit existing EO/IR data lakes and implement cross-attention mechanisms.
• Sync with Data Engineers on ingestion pipelines.
• Collaborate with the Edge AI team to ensure high-performance model handoffs.
• Architect state machines for fault-tolerant data pipelines.
• Mediate technical trade-offs between hardware and algorithm teams.

Required qualifications

• PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics.
• 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).
• Hardcore PyTorch engineering skills.
• Deep mathematical intuition for representation learning.
• Knowledge of system-level languages (C++, Rust, or Go).
• Knowledge of resource optimisation for edge computing.
• Ability to architect state machines for fault-tolerant data pipelines.
• Ability to mediate technical trade-offs between hardware and algorithm teams.
• 100% dedication to Harmattan AI’s mission of providing an ethical defence edge to allied countries.
• A hybrid researcher-engineer mindset.

About the company

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. The company is expanding its teams to deliver mission-critical systems to allied forces.