Machine Learning Engineer - Foundational
Core
Design and scale large-scale, multi-modal foundational models using Self-Supervised Learning (SSL) from unlabelled Electro-Optical (EO) and Infrared (IR) data to build the 'brain' of tactical robots.
Role type
Senior IC machine learning engineer (multi-modal SSL)
Builds
Foundational model weights for tactical robot autonomy
Domain
Defense / Computer Vision / Multi-modal Learning
Deliverable
production ML models
Required skills
Self-Supervised Learning (SSL), Vision Transformers (ViTs), Masked Autoencoders, Contrastive Learning, multi-GPU distributed training, PyTorch, C++, Rust, Go, representation learning, data lake auditing, cross-attention mechanisms
Preferred skills
Experience with non-standard imaging data (IR, SAR, hyperspectral), system-level resource optimization for edge computing, state machine architecture
Technologies
PyTorch, Vision Transformers, Masked Autoencoders, C++, Rust, Go
Responsibilities
Design neural network architectures and loss functions for joint EO/IR learning; Manage and optimize training pipelines across multi-node GPU clusters; Develop metrics and linear-probing benchmarks for latent space evaluation; Audit EO/IR data lakes and implement cross-attention mechanisms; Collaborate with Data Engineers and Edge AI teams on model handoffs
Seniority
Senior, hands-on IC