Senior ML Engineer - Multi-Modal SSL & Vision Transformers

Harmattan AI; Zürich; On-site; CHF 110,000 - 150,000; Full time

Job summary

Harmattan AI is seeking a Machine Learning Engineer to join our Foundational team in Zürich. You will create large-scale models for tactical robots, leveraging Self-Supervised Learning with Electro-Optical and Infrared data. Your contributions will be instrumental in delivering cutting-edge solutions for allied forces.

We require a PhD or a highly research-focused MS with 5+ years of experience in deep learning, proficiency in PyTorch, and a hybrid researcher-engineer mindset. Join us to shape the future of autonomous defense systems.

Qualifications

• Minimum of 5-6 years of experience for senior levels.
• Experience training and scaling deep learning vision models (ViTs, CNNs) in multi-GPU/multi-node environments.
• Successful application of novel SSL or multi-modal architectures (e.g., CLIP, MAE, DINO) to non-standard imaging data.

Responsibilities

• Design neural network architectures for Multi-Modal SSL.
• Manage and optimize distributed training infrastructure.
• Develop metrics to evaluate representation learning.
• Audit EO/IR data lakes and implement cross-attention mechanisms.
• Collaborate with Data Engineers and Edge AI team.

Skills

PyTorch engineering skills

Deep mathematical intuition

C++, Rust, or Go knowledge

Representation learning

Education

PhD or highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics

Job description

Harmattan AI is seeking a Machine Learning Engineer to join our Foundational team in Zürich. You will create large-scale models for tactical robots, leveraging Self-Supervised Learning with Electro-Optical and Infrared data. Your contributions will be instrumental in delivering cutting-edge solutions for allied forces.

We require a PhD or a highly research-focused MS with 5+ years of experience in deep learning, proficiency in PyTorch, and a hybrid researcher-engineer mindset. Join us to shape the future of autonomous defense systems.