Cerebras Systems~19d ago

ML Research Engineer (Inference)

India·Bangaloremid

OtherAi Research EngineerData & AIMl Research Engineer

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Quick Summary

Overview

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip,

Technical Tools

OtherAi Research EngineerData & AIMl Research Engineer

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include top 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.

Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.

About the Role

~1 min read

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

Requirements

~1 min read

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
1–3 years of experience in software engineering or machine learning in a similar capacity (internships count)
Experience with Python and at least one ML framework (e.g., PyTorch, Transformers, vLLM or SGLang)
Understanding of deep learning concepts (e.g., neural networks, transformers)
Experience with Generative AI and Machine Learning systems
Strong programming skills in Python and/or C++

Requirements

~1 min read

Experience with speculative decoding, neural network pruning and compression, sparse attention, quantization, sparsity, post-training techniques, and inference-focused evaluations.
Exposure to large language models or computer vision models
Experience running experiments or tuning models
Familiarity with tools like PyTorch, Hugging Face Transformers, or similar
Basic understanding of performance concepts (e.g., latency, throughput)
Experience working in Linux environments

What We Offer

~1 min read

✓Build a breakthrough AI platform beyond the constraints of the GPU.

✓Publish and open source their cutting-edge AI research.

✓Work on one of the fastest AI supercomputers in the world.

✓Enjoy job stability with startup vitality.

✓Our simple, non-corporate work culture that respects individual beliefs.

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 them.

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