Advance vision-language models at Mecka AI through multimodal research, post-training, and reinforcement learning for embodied AI systems. This experienced Research Scientist will develop large-scale multimodal foundation models across their development lifecycle. You will research architectures, training strategies, evaluation methods, and optimization techniques. The work connects data quality, model reasoning, reliability, and real-world capabilities.

Key Responsibilities
Research and improve vision-language model architectures Implement supervised fine-tuning, preference optimization, and reinforcement learning Investigate reasoning, generalization, reliability,



and training efficiency Design evaluations and benchmarks to identify model failure modes Run experiments with distributed infrastructure and large datasets

Requirements:
Hands-on experience training large-scale multimodal foundation models Experience with Qwen, Qwen-VL, or comparable models Solid understanding of deep learning and optimization Proficiency in Python and PyTorch, JAX, or comparable frameworks Experience analyzing large-scale machine learning experiments Bring multimodal model research, reinforcement learning, and evaluation expertise to Mecka AI’s embodied AI systems.

📌 Multimodal Foundation Model Scientist (Canada)
🏢 mecka
📍 Canada