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Cerebras Systems, Bengaluru-based, seeks a Research Engineer for the Inference ML team to adapt language and vision models to Cerebras architecture. You’ll work with ML researchers to prototype, validate, and optimize models for low-latency, high-throughput inference on the world’s fastest AI accelerator.
You will explore speculative decoding, pruning, sparse attention, and sparsity-driven techniques to push the frontier of efficient large-model inference at scale, collaborating across ML,
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry‑leading training and inference speeds; over 10 times faster than GPU‑based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real‑time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting‑edge AI‑native startups. OpenAI recently announced a multi‑year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high‑speed inference.
As a Research Engineer on the Inference ML team at Cerebras Systems, you will adapt today's most advanced language and vision models to run efficiently on our flagship Cerebras architecture. You'll work alongside ML researchers and engineers to design, prototype, validate, and optimize models, gaining end‑to‑end exposure to cutting‑edge inference research on the world's fastest AI accelerator.
You will focus on pushing the frontier of speculative decoding, large‑model pruning and compression, sparse attention, and sparsity‑driven techniques to deliver low‑latency, high‑throughput inference at scale.
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around us.