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Machine Learning Engineer - Foundational

Harmattan AI· R&D
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ZurichFull-timePosted 4mo ago

About the role

Machine Learning Engineer on the Foundational team responsible for building and scaling large-scale, multi-modal foundational models for tactical robots using Self-Supervised Learning on unlabelled EO/IR data, providing foundational weights for Edge AI deployment.

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.

Qualifications

  • A 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 with deep mathematical intuition for representation learning.
  • Knowledge of system-level languages (C++, Rust, or Go) and resource optimisation 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 and a hybrid researcher-engineer mindset that values data quality as seriously as algorithm design

Skills

Required:Vision Transformers (ViTs)Self-Supervised LearningMulti-Node GPU TrainingPyTorchSystems/Edge Computing
Nice to have:Data Engineering Collaboration
Last updated Jul 15, 2026. Interested? Apply on the company site.
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About Harmattan AI

Building the Future of Autonomous Warfare.

Building the Future of Autonomous Warfare.

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