Lead Full Stack Machine Learning Engineer

Cerebras; Bengaluru; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Cerebras is looking for an experienced professional to rapidly bring up state-of-the-art open-source models and frameworks. The role requires a system-minded generalist who can work across the software stack ensuring high performance and scalability for AI applications.

The ideal candidate has 10+ years of experience in fields such as Computer Science or Engineering, proficiency in C/C++, and is comfortable with deep learning frameworks like PyTorch and TensorFlow. Strong debugging and optimization skills are essential for success in this role.

Qualifications

• 10+ years’ experience in Computer Science or related field.
• Strong debugging skills across performance and numerical accuracy.
• Experience with AI toolchain and low-level optimization.

Responsibilities

• Contribute to the end-to-end bring up of frameworks for AI models.
• Work across the stack from architecture to performance tuning.
• Debug performance and correctness issues across model code and hardware utilization.
• Propose improvements for future bring ups.

Skills

Performance profiling

Debugging skills

C/C++ programming

Deep learning frameworks (e.g., PyTorch, TensorFlow)

Optimization techniques

Education

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

Tools

Python

Job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs, delivering industry-leading training and inference speeds. This order of magnitude increase in speed transforms the user experience of AI applications, unlocking real-time iteration and increased intelligence via additional agentic computation.

This role focuses on rapidly bringing up state-of-the-art open-source models, frameworks, and data engineering. Success requires a system-minded generalist who thrives in fast-paced bring-up environments and works across the entire software stack to achieve high performance, efficiency, and scalability for AI applications.

Responsibilities

• Contribute to the end-to-end bring up of frameworks for RL, inference serving, and 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.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field with 10+ years’ experience.
• Comfort navigating the full AI toolchain: Python modelling 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.
• Strong background in optimization techniques, particularly those involving NP-hard problems.