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As an ML Quality Engineer, 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.
Job Responsibility:
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
Requirements:
3-7 years of relevant industry experience in Software quality and testing areas
Experience testing AI/ML models and evaluation of the model quality
Strong 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
Nice to have:
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
What we offer:
Build a breakthrough AI platform beyond the constraints of the GPU
Publish and open source their cutting-edge AI research
Work on one of the fastest AI supercomputers in the world
Enjoy job stability with startup vitality
Our simple, non-corporate work culture that respects individual beliefs