Full Stack LLM Engineer

About the role

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 https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About the Role We are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.

Responsibilities

- Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.

- Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.

- Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.

- Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.

Skills & Qualifications

- Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.

- Comfort navigating the full AI toolchain: Python modeling code, compiler IRs, performance profiling, etc.

- Strong debugging skills across performance, numerical accuracy, and runtime integration.

- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).

- Proficiency in C/C++ programming and experience with low-level optimization.

- Proven experience in compiler development, particularly with LLVM and/or MLIR.

- Strong background in optimization techniques, particularly those involving NP-hard problems.

What We Offer

- Competitive salary and benefits package.

- Opportunities for professional growth and career advancement.

- A dynamic and innovative work environment.

- The chance to work on cutting-edge technologies and make a significant impact on the future of AI.

Why Join Cerebras