Machine Learning Research Scientist

• Conduct original research in machine learning and AI with a focus on models that integrate multiple modalities.
• Develop, train, and fine-tune large language models (LLMs) and multi-modal models (MMMs).
• Explore and scale trillion-parameter neural networks, along with smaller, specialized models.
• Design and implement models capable of solving discrete and continuous constraint reasoning tasks and graph-related challenges.
• Develop and evaluate interconnected systems comprising LLMs, NLP models, and retrieval algorithms.
• Publish research findings in top AI conferences and journals, contributing to the academic and industry community.
• Collaborate with cross-functional teams to translate research outcomes into practical applications.
• Innovate and create data synthetically and collect it from human interactions for diverse tasks.
• Lead efforts in optimizing both open-source and proprietary models, considering various constraints.
• Required Skillsets
• Strong background in machine learning, including sequence modeling, generative models, and model architecture.
• Expertise in Pytorch, Python, CUDA, and Triton.
• Proven research experience with a strong publication record in top AI conferences and journals.
• Deep understanding of pre-training and fine-tuning large multi-modal models.
• 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.

None flagged.