ML Software Engineer - Integration & Quality - New Grad

About the Role

We are looking for a new graduate or early-career Software Engineer to join the ML Integration and Quality team at Cerebras. This team works at the intersection of machine learning infrastructure, distributed systems, and hardware/software co-design. In this role, you will help integrate, test, and validate the software stack that powers the Cerebras AI platform. You will work alongside experienced engineers across runtime, compiler, kernel, infrastructure, and hardware teams to investigate issues, build automation, and improve the reliability of large-scale machine learning workloads. This is an excellent opportunity for an early-career engineer who enjoys solving technical problems, learning how complex systems work, and gaining hands-on experience with large-scale AI infrastructure.

Responsibilities

• Help integrate and validate software components across the Cerebras AI platform.
• Develop automated tests and tools that support software integration, system validation, and release quality.
• Investigate software failures, test regressions, and unexpected system behavior with support from senior engineers.
• Collaborate with engineers across ML runtime, compiler, kernel, infrastructure, and hardware teams.
• Contribute to the development and maintenance of testbeds used to validate system functionality, performance, and reliability.
• Help reproduce, document, and troubleshoot issues across different layers of the ML software stack.
• Contribute to test plans and validation strategies for new features and platform capabilities.
• Improve internal tooling, diagnostics, logging, and debugging workflows.
• Analyze test results and system data to identify failure patterns, edge cases, and opportunities for improvement.
• Participate in code reviews, technical discussions, and team development processes.
• Learn about distributed systems, machine learning infrastructure, and hardware/software interactions while contributing to production software.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, or a related technical field.
• Strong programming fundamentals in Python, C++, Go, Java, or a similar language.
• Understanding of core computer science concepts, including data structures, algorithms, operating systems, or computer architecture.
• Experience debugging software through internships, research, or co-op placements.
• Familiarity with software development practices such as version control, unit testing, and code reviews.
• Strong analytical and problem-solving skills.
• Interest in working across multiple areas of a complex software system.
• Ability to communicate clearly and collaborate effectively within a technical team.
• Curiosity, attention to detail, and a willingness to learn new technologies.

Preferred Qualifications

• Internship, co-op, research, or project experience in software engineering, systems engineering, infrastructure, or machine learning.
• Exposure to machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Familiarity with Linux development environments and command-line tools.
• Exposure to distributed systems, networking, cloud infrastructure, or large-scale compute environments.
• Experience building test automation, developer tools, or internal software utilities.
• Familiarity with containers or orchestration technologies such as Docker or Kubernetes.
• Exposure to debugging, profiling, monitoring, or observability tools.
• Understanding of compilers, computer architecture, hardware accelerators, or parallel computing.
• Interest in large language models, multimodal models, or machine learning model deployment.

Schedule

This role follows a hybrid schedule and requires in-office presence three days per week. Fully remote work is not available.

Location

• Sunnyvale, California
• Toronto, Ontario

Why Join Cerebras

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source cutting-edge AI research.
• Work on one of the fastest AI supercomputers in the world.
• Enjoy job stability with startup vitality.
• A simple, non-corporate work culture that respects individual beliefs.