DeveloperRelationsManager,HigherEducationandResearchAIAgents

PhD in Computer Science, AI, Machine Learning, Applied Mathematics, Electrical Engineering, or a related technical field, or equivalent research depth, 5+ years of experience, Deep expertise in foundational AI, including LLMs, multimodal models, generative AI, reasoning, post-training, model evaluation, or AI systems research, Understanding of modern AI model development across the lifecycle, including pretraining, fine-tuning, post-training, optimization, evaluation, deployment, and model serving, Hands-on experience with AI research stacks such as PyTorch, JAX, distributed training frameworks, inference systems, model serving platforms, evaluation pipelines, and GPU-accelerated workflows, Technical fluency in scalable AI systems, including distributed training, parallelism strategies, checkpointing, memory optimization, batching, scheduling, latency, throughput, and cost-performance tradeoffs, Familiarity with methods that improve model efficiency and performance, such as quantization, distillation, sparsity, speculative decoding, attention optimization, synthetic data generation, RLHF/RLAIF, and preference optimization, Ability to engage top academic labs on frontier research challenges, including scaling behavior, compute efficiency, model quality, benchmark methodology, reproducibility, reliability, and research impact, Demonstrated research credibility through publications, open-source contributions, academic collaborations, technical leadership, or direct work on frontier AI systems