Cerebras has developed a radically new chip and system to dramatically accelerate deep learning applications. Our system runs training and inference workloads orders of magnitude faster than contemporary machines, fundamentally changing the way ML researchers work and pursue AI innovation.

We are innovating at every level of the stack – from chip, to microcode, to power delivery and cooling, to new algorithms and network architectures at the cutting edge of ML research. Our fully-integrated system delivers unprecedented performance because it is built from the ground up for deep learning workloads.

Role

As a hardware-focused Data Engineer, you will improve and maintain the data infrastructure that extracts actionable insights from hardware manufacturing and test data. This role is highly collaborative and cross-functional, and directly impacts the development and manufacturing of Cerebras wafer-scale computing systems. You will work alongside the best electrical, mechanical, and system engineers in the industry and help them make effective data-driven decisions. You will ingest, manage, and analyze a diverse assortment of data with the latest and most advanced data processing technologies. 

Responsibilities 

• Develop and maintain highly reliable data processing pipelines using Python, SQL, and various technology platforms such as Airflow and the ELK stack. 
• Manage, analyze, and serve ever-increasing volumes of high-quality data using backend databases such as PostgreSQL and MySQL and frontend tools such as Grafana, Jupyter, and Redash. 
• Continuously improve the efficiency and effectiveness of Cerebras hardware manufacturing by taking ownership of data from end to end. 
• Partner with hardware and system engineers to translate data insights into effective decision making while identifying opportunities for automation. 
• Continually evaluate team processes to maintain an efficient and performant data-driven engineering culture. 

Skills & Qualifications

• Bachelor's degree in computer science, mathematics, or related field. 
• 2+ years of backend engineering experience, including advanced database operations with SQL. 
• 2+ years of software development experience with Python, including agile development practices (e.g. issue lifecycle management, change control, code review). 
• Experience with a variety of technologies and ability to pick the right tool for the job. 
• Ability to communicate and collaborate with cross-functional partners on data processing and analysis projects. 
• Ability to bring thoughtful perspectives, creativity, and a positive attitude to solve problems at scale. 

Preferred Qualifications

• Advanced degree in computer science, mathematics, or related field. 
• Experience with cloud computing services such as AWS or Google Cloud. 
• Experience with Python data processing libraries such as Pandas. 
• Experience with designing and developing custom ETL processes and pipelines. 
• Experience with designing and developing APIs in Python. 
• Experience with transfer, storage, and analysis of real-time telemetry data. 
• Experience with DevOps tools such as infrastructure-as-code (IaC) tools or CI/CD tools. 

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

Read our blog: Five Reasons to Join Cerebras in 2024.

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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