QA Lead (ML Integration and Quality)

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 with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About The Role 

As an ML QA Lead, you ensure quality of Cerebras SW across all supported ML workloads and workflows. You will be part of MIQ (ML Integration and Quality) team that will focus on SW components feature testing, ML training accuracy and performance, pre deployment/production validation, validating customer workloads and workflows.

As part of this role, you will influence the best testing practice, good debugging methodology, effective cross team communication and advocate for world-class products.

Responsibilities

• Drive quality of various software and hardware components of Cerebras solution to ensure accuracy, performance and usability of model trainings.

• Bring good testing methodology, effective communication and strong debugging skills to the team.

• Demand the highest quality from all components within the Cerebras environment.

• Ability to automate workflows, setup testbeds and build tools to effectively monitor and debug issues.

• Implement creative ways to break Cerebras software and identify potential problems.

• Break down complex tasks into smaller tasks. Be a problem solver. Be a thought leader.

• Ability to work in a fast-paced environment and make the necessary prioritizations and judgements which affects productivity at a company level.

Skills & Qualifications

• 8 years of relevant industry experience in Software quality and testing areas.

• Experience testing AI/ML models and evaluation of the model quality.

• Stong automation and programming skills using one or more programming languages like Python, C++ or go.

• Experience in testing compute/machine learning/networking/storage systems within a large-scale enterprise environment.

• Experience in debugging issues across scale out deployment.

• Experience in putting together thorough test-plans.

• Experience working effectively across teams, including product development, product management, customer operations, and field teams.

Preferred Skills & Qualifications

• Knowledge of ML workflows and frameworks.

• Knowledge of basic storage and networking protocols.

• Hands-on experience with training LLMs.

• Hands-on experience working with containers, Kubernetes.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

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

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

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

4. Enjoy job stability with startup vitality.

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

Find out more about what it’s like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in 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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