Join Helsing as a Senior AI Research Engineer to design, train, and fine-tune large-scale Vision-Language Models (VLMs) for autonomous defense capabilities. Focus on multimodal sensor data, model lifecycle management, and cutting-edge research in foundational AI. Requires deep expertise in LLMs/VLMs, Python, and distributed deep learning frameworks like PyTorch/JAX.
Key Highlights
Research, design, and train large-scale Vision-Language Models (VLMs) for autonomous defense applications
Full ownership of model lifecycle: data curation, training, fine-tuning, and evaluation
Work at the intersection of AI research and engineering with a focus on multimodal foundational models
Key Responsibilities
Research and design large-scale Vision-Language Models (VLMs) to process multimodal sensor data for autonomous defense systems
Curate, clean, and prepare custom datasets for training and fine-tuning VLMs
Develop and optimize distributed training pipelines for large-scale models using PyTorch/JAX
Implement custom layers, loss functions, and training loops for advanced model architectures
Evaluate and iterate on model performance, ensuring robustness, safety, and ethical compliance
Collaborate with cross-functional teams to integrate models into defense products and systems
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Benefits & Perks
Competitive salary and VSOP options
Relocation support: up to €2,500 and 4 weeks temporary accommodation
€500 yearly learning allowance
Health & wellness: gym membership and mental health support (Nilo.health)
Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers
Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
Regular company events and monthly social allowances
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Nice to Have
Top-tier research publications in NeurIPS, ICML, ICLR, CVPR, or ACL (focus on attention mechanisms, efficient transformers, or multimodal learning)
Experience training models on large-scale GPU clusters
Proven expertise in data curation, cleaning, pruning, and building robust data pipelines for large-scale datasets
