ML API Features SDET

<div class="content-intro"><p><span data-contrast="none">Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. </span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335559685":0,"335559737":240,"335559738":240,"335559739":240,"335559740":279}"> </span></p> <p>Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. <a href="https://openai.com/index/cerebras-partnership/">OpenAI recently announced a multi-year partnership with Cerebras</a>, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. </p> <p>Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.</p></div><p><strong>About The Role</strong></p> <p>As a Software Engineer in Test for the ML API features team, you will be involved in testing AI/ML models for accuracy, fairness, and performance. You will play a pivotal role in bringing together and delivering all software and hardware components for Cerebras API Features. You will focus on SW components feature integration and quality and Pre-deployment/production validation for Cerebras inference solution. 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.</p> <p> <strong>Responsibilities</strong></p> <ul> <li>Understand new features end-to-end, and develop tests and tools to ensure quality.</li> <li>Contribute to industry standard benchmarks.</li> <li>Drive automation to improve internal efficiency.</li> <li>Understand trade off between coverage and resource requirements.</li> <li>Work in a highly agile environment where priorities change frequently.</li> <li>Effectively communicate across teams and timezones.</li> </ul> <p><strong>Skills Qualifications</strong></p> <ul> <li>2+ years of relevant industry experience in Software integration, development or quality.</li> <li>Strong automation and programming skills using one or more programming languages like Python, C++ or go.</li> <li>Experience in testing compute/machine learning/networking/storage systems within a large-scale enterprise environment.</li> <li>Experience in debugging issues across distributed scale out deployment.</li> <li>Experience working effectively across teams, including product development, product management, customer operations, and field teams.</li> <li>Excellent verbal and written communication skills.</li> <li>Strong organizational skills, teamwork, and can-do attitude.</li> <li>Experience working with geographically dispersed teams across time zones.</li> </ul> <p><strong>Preferred Skills Qualifications</strong></p> <ul> <li>Experience in working with ML workloads such as LLM/Multimodal training or inference.</li> <li>Experience with hardware architecture, performance optimizations, compilers and ML frameworks.</li> <li>Experience working with distributed systems, cloud and security.</li> <li>Experience working with microservices deployment, debugging and orchestration. </li> </ul> <p><strong>Location</strong></p> <ul> <li>This role follows a hybrid schedule, requiring in-office presence 3 days per week. Please note, fully remote is not an option.</li> <li>Office lo ... (truncated, view full listing at source)