We're partnering with a portfolio of exceptionally well-funded AI companies operating at the frontier of machine learning research. Founded by leading researchers, repeat founders, and industry veterans, these organizations are developing next-generation foundation models, reasoning systems, multimodal AI, agentic systems, and advanced training methodologies. These teams are tackling some of the most important challenges in artificial intelligence, including large-scale pre-training, post-training, reinforcement learning, alignment, reasoning, model architecture innovation, synthetic data generation, and scalable training systems. They are backed by top-tier investors and are building technologies with the potential to reshape industries and advance the state of the art in AI. Who We're Looking For PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Physics, Electrical Engineering, or a closely related field. Strong publication record at top-tier venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, ECCV, MLSys, CoRL, RSS, or equivalent. Demonstrated history of conducting novel research and driving projects from idea through publication. Strong coding and experimentation skills, typically in Python and modern ML frameworks such as PyTorch or JAX. Deep understanding of modern foundation models and large-scale machine learning systems. Research Areas of Interest Large-scale pre-training of language, multimodal, and foundation models. Post-training, instruction tuning, preference optimization, alignment, and reasoning optimization. Reinforcement Learning, RLHF, RLAIF, online RL, offline RL, and scalable RL systems. Mid-training and continual learning methodologies. Model architecture research and training efficiency. Synthetic data generation and data curation. Evaluation, benchmarking, reward modeling, and model alignment. Agentic systems and reasoning-focused models. Preferred Background Publications at leading machine learning conferences and journals. Experience at top AI labs, research organizations, universities, or frontier AI startups. Experience training, evaluating, or improving large-scale foundation models. Open-source contributions, influential research artifacts, or widely adopted technical work are a strong plus. What You'll Do Conduct cutting-edge AI research aimed at advancing the state of the art. Design novel training methodologies and model architectures. Publish research at leading conferences and journals. Collaborate with world-class researchers, engineers, and founders. Help shape the research agenda and technical direction of high-impact AI organizations. Translate breakthrough research into systems and products used at scale. Why Apply You’ll gain access to opportunities with some of the most ambitious AI companies currently hiring. These teams are exceptionally well-capitalized, deeply research-oriented, and focused on solving fundamental problems in artificial intelligence. Compensation is highly competitive and typically includes substantial equity participation alongside the opportunity to work with world-class research teams. #J-18808-Ljbffr
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