# ML Research Scientist - Inference ML at Cerebras Systems

- Company: Cerebras Systems
- What the company does: Cerebras powers the world's fastest AI inference on the biggest wafer chip. Cerebras CS-4 delivers up to 30x faster inference than GPUs.
- Company website: https://www.cerebras.ai
- Type: Startups (AI role)
- Level: Mid level
- Location: United States and Canada
- Work setup: On-site
- Posted: 2026-10-02
- Apply by: 2026-11-23
- Apply: https://jobs.ashbyhq.com/cerebras/cb57dac6-84cc-4860-9732-39c60514a2ab?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/cerebras-systems-senior-research-engineer-inference-ml/

## About the role

As an ML Research Scientist on the Inference ML team at Cerebras Systems, you will invent and evaluate advanced algorithms, methods and model architectures for efficient inference on our flagship Cerebras architecture. You'll work alongside ML researchers and engineers to design, prototype, validate, and optimize methods and models, contributing to cutting-edge inference research on the world's fastest AI accelerator. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- PhD in machine learning, computer science, or a closely related technical field with 3+ years of relevant research or industry experience, OR a master’s degree with an exceptional record of original, independent research and 4+ years of relevant experience
- Deep understanding of modern ML architectures and generative models in language and/or vision domains, machine learning systems, and the principles that govern their inference behavior
- Ability to reason about model and algorithm performance, particularly for inference workloads
- Ability to identify practically relevant research questions, develop novel methods, and evaluate their effects on model quality and inference efficiency
- Strong Python programming skills and proficiency with relevant ML frameworks such as PyTorch, Transformers, vLLM, or SGLang
- Original research in one or more of: speculative decoding , neural network pruning and compression , sparse attention , quantization, mixture-of-experts models, sparsity , post-training techniques, or inference-aware design

Tags: Software Engineering

Source: 1752vc Careers, https://www.1752.vc/careers/jobs/cerebras-systems-senior-research-engineer-inference-ml/