Machine Learning Research Engineer

• Train foundation models from scratch that integrate multiple modalities.
• Train and fine-tune large language models (LLMs) and multi-modal models (MMMs).
• Design and implement models capable of solving discrete and continuous constraint reasoning tasks and graph-related challenges.
• Structure and optimize data for model training, ensuring high performance and efficiency.
• Create data synthetically and collect it from human interactions for diverse tasks.
• Build and optimize both open-source and proprietary models, considering various constraints.
• Design and execute innovative search and retrieval algorithms.
• Required Skillsets
• Strong software engineering skills, particularly in Pytorch, Python, CUDA, and Triton.
• Deep expertise in machine learning, including sequence modeling, generative models, and model architecture.
• Experience in pre-training and fine-tuning large multi-modal models.
• Proven track record of publications in top AI conferences and competitions.
• Experience implementing research papers into production code.
• Familiarity with the latest state-of-the-art techniques, including prompting and inference-time search methods.
• Experience in developing and managing large-scale machine learning systems.
• Proficiency in configuring and optimizing hardware and operating systems for maximum performance.
• Experience building distributed training systems for AI models in high-performance computing (HPC) clusters.

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