Mixture of Experts Jobs

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Their work integrates model training, inference algorithms, and serving systems, optimizing all three for reduced cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your solutions against realistic serving workloads, such as long-context and agentic traffic.

Together AI

The Speculative Decoding team at Together AI focuses on developing draft models and algorithms to accelerate large language model generation without altering outputs. Our work spans model training, inference algorithms, and serving systems, aiming to reduce generation cost and latency. As a research intern, you will explore open questions in speculative decoding, including new drafter architectures, verification schemes, knowledge distillation, and adaptive drafters. You will train and fine-tune draft models at scale on GPU clusters and evaluate your ideas against realistic serving workloads, such as long-context and agentic traffic. Projects are designed to address key research questions in speculative decoding, leading to faster generation on frontier models, drafters that adapt to changing workloads, and robust evaluation under real traffic.

Aleph Alpha is seeking a Senior AI Researcher to join their Pre-training team, focusing on advancing the architecture and training of next-generation foundation models. This role involves designing inference-efficient architectures, optimizing large-scale training recipes, and working with thousands of NVIDIA GPUs. The position is ideal for someone excited about the intersection of research and engineering, translating mathematical reasoning into principled training decisions from small-scale experiments to large-scale runs. The researcher will influence model quality, run reliability, and efficiency by combining rigorous experimental design with high-quality production code.

As a Senior Principal Machine Learning Engineer, you will be responsible for designing, developing, and optimizing machine learning models, with a focus on cutting-edge Large Language Models (LLMs), to run efficiently on SambaNova's specialized hardware architecture, including the RDU. This critical role bridges advanced LLM research and practical deployment, involving the development of model architectures, improving training and inference efficiency, and collaborating on hardware-software co-design with compiler, systems, and hardware teams. The engineer will also act as the ML expert, guiding the integration of LLM solutions into production systems and customer-facing products like SambaStack and SambaCloud, with work spanning the full lifecycle from training and inference to evaluation and data curation.

$220k - $300k