Machine Learning Engineer - Foundational

Harmattan AI
Zurich
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5-6 yearsEducation: phdSkills: ["PyTorch","Vision Transformers","CNNs","Linear probing","Multi-node distributed training","Edge computing","Data ingestion"]

Machine Learning Engineer on the Foundational team to design and scale multi-modal SSL models (EO/IR) for tactical robots. You’ll build Vision Transformers, run distributed multi-node GPU training, and develop evaluation metrics, data strategies, and cross-functional handoffs to deliver foundational weights for edge AI deployments in a defense context.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Harmattan AI
Harmattan AI
3 months ago

Machine Learning Engineer - Foundational

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 15 minutes agoStatus: Live

Job Summary

Machine Learning Engineer on the Foundational team to design and scale multi-modal SSL models (EO/IR) for tactical robots. You’ll build Vision Transformers, run distributed multi-node GPU training, and develop evaluation metrics, data strategies, and cross-functional handoffs to deliver foundational weights for edge AI deployments in a defense context.
Location: Zurich
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key 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.

Key Requirements

  • •PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics
Experience:5-6 yearsDefenseAutonomous systemsMultimodal ML
Education:PhD / Doctorate in Computer Science
Skills:PyTorchVision TransformersCNNsLinear probingMulti-node distributed trainingEdge computingData ingestion
Tech Stack:PyTorchVision TransformersMAEDINOCLIPCNNsC++RustGoGPUMulti-nodeDistributed training

Company Brief

Harmattan AI
Develops AI-driven autonomous military systems (drones, electronic warfare, ISR and mission-management software) and scales conflict-ready production for allied armed forces and defense primes.
Industry: Defense Technology
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series B
Headquarters: Paris, France
Founded: 2024
WebsiteLinkedInGlassdoor