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.
About The Role
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.
Responsibilities
Implement and adapt transformer-based models (NLP and/or vision) to run on Cerebras hardware
Assist in optimizing models for inference performance (latency, throughput)
Run experiments, analyze results, and support model improvements
Help bring up and validate models on the Cerebras system
Debug and troubleshoot model or system issues with guidance from senior team members
Support profiling and performance analysis using internal tools
Collaborate with cross-functional teams (ML, software, hardware) on model integration

Minimum Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
1–3 years

📌 Ml Research Engineer Bengaluru
🏢 Cerebras Systems
📍 Bengaluru