ML Research Scientist - Inference ML

Job summary

Responsibilities

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.

• Research and prototype novel inference algorithms and model architectures that exploit the unique capabilities of Cerebras hardware, with emphasis on speculative decoding…
• Design and evaluate new transformer architectures and variants for NLP and computer vision to improve the trade-offs among quality, latency, throughput, and compute.
• Identify and pursue high-impact research directions at the intersection of model architecture, inference systems and hardware.
• Train or adapt models where needed, and measure and analyze inference performance using Cerebras tools to maximize throughput and minimize latency.
• Collaborate with engineering and performance teams to understand practical constraints and help translate successful research into usable systems, from inception through delivery.

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…
• 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…
• 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.
• Evidence of research impact in machine learning, statistics, information theory, or a closely related field, with clear relevance to modern ML, through publications in leading…

Tech stack

• Python
• PyTorch
• Transformers
• vLLM
• Triton
• CUDA
• C++