Data Platform Engineer

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.  

Cerebras' current customers include top 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. 

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.

About the Role 

As a Platform Engineer on the Cerebras Data Analytics team, you will design, build, and maintain a reliable, high-performance cloud data platform that enables the company’s success via data-driven insights. Your work will amplify the impact of data engineers and data scientists to address diverse needs across hardware, software, operations, and business intelligence. The ideal candidate is a proactive, independent problem solver who takes pride in delivering efficient and effective solutions. 

Responsibilities 

• Design, deploy, and maintain core infrastructure in AWS for data storage, processing, and reporting. 

• Maintain and scale databases and data lakes that store ever-increasing volumes of data. 

• Create tools, automations, and frameworks to improve developer efficiency. 

• Create monitoring and alerting systems to effectively identify risks and quickly resolve issues. 

• Continuously improve the reliability, scalability, and cost-effectiveness of the entire data platform. 

• Collaborate cross-functionally with IT, Security, and engineering teams to securely integrate data sources and infrastructure in various locations. 

Skills and Qualifications 

Required 

• 3+ years of professional experience in platform engineering, reliability engineering, DevOps, or an infrastructure-focused role. 

• 3+ years of hands-on experience in AWS, especially EC2, S3, CloudWatch, and/or IAM. 

• Proficiency in at least one advanced programming language (e.g. Python, C++). 

• Experience with relational SQL databases (e.g. PostgreSQL, MySQL). 

• Experience with Infrastructure-as-Code platforms (e.g. Terraform, AWS CloudFormation). 

• Experience with Git. 

Preferred 

• Strong proficiency in Python. 

• Experience with data engineering, data analytics, and/or business intelligence. 

• Experience with containerization tools and platforms (e.g. Docker, Kubernetes). 

• Experience with monitoring/observability tools and platforms (e.g. Datadog, Splunk, Prometheus, Loki, Grafana). 

• Experience with front-end technologies and frameworks (e.g. HTML, JavaScript). 

• Experience with networking and cybersecurity. 

The base salary range for this position is $160,000 to $250,000 annually.  Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.

 

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