Full Stack LLM Engineer

Foundation Capital; Toronto; On-site; CAD 80,000 - 120,000; Full time

Benefits offered by this job

Competitive salary and benefits package

Opportunities for professional growth

Dynamic and innovative work environment

Job summary

A leading AI technology company in Toronto is seeking a versatile engineer to join their Inference Core Model Bringup team. This role involves bringing state-of-the-art models onto the Cerebras CSX systems, requiring experience in Python, compiler IRs, and strong debugging skills. Ideal candidates should have a degree in Computer Science or Engineering, and enjoy working in fast-paced environments. Benefits include a competitive salary and a chance to work with cutting-edge technologies.

Qualifications

• Experience with deep learning frameworks such as PyTorch and TensorFlow.
• Strong debugging skills necessary for performance and runtime integration.
• Proficiency in C/C++ programming with emphasis on low-level optimization.

Responsibilities

• Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.
• Work across model architecture translation, compiler optimizations, and performance tuning.
• Debug performance and correctness issues related to models and hardware utilization.

Skills

Debugging skills

C/C++ programming

Python modeling code

Deep learning frameworks

Performance profiling

Education

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

Tools

LLVM

MLIR

Job description

About the Role

We are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible for rapidly bringing 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 bring‑up 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.

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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