Build the next generation of foundation-model capabilities at Mecka AI using Python, PyTorch, large-scale experiments, and advanced post-training. This experienced Research Scientist will work with large-scale datasets and distributed training infrastructure. You will train, fine-tune, and evaluate multimodal models, including Qwen or comparable open-weight systems. The role emphasizes practical experimentation, data quality, reinforcement learning, and measurable model improvements.

Key Responsibilities
Train and post-train large-scale multimodal foundation models Design data curation, filtering,



and synthetic-data generation strategies Execute and analyze large-scale machine learning experiments Investigate model optimization and performance improvements Explore reward modeling and advanced model evaluation

Requirements:
Experience with Qwen, Qwen-VL, or comparable open-weight models Proficiency in Python and PyTorch, JAX, or similar frameworks Experience with supervised fine-tuning or reinforcement learning Familiarity with multimodal images, video, or sensory-data pipelines Publications, open-source contributions, or leading AI organization experience Use foundation-model training, data strategy, and experiment analysis skills to advance multimodal AI research at Mecka AI. #J-18808-Ljbffr

📌 Foundation Model Research Scientist (Richmond Hill)
🏢 mecka
📍 Richmond Hill