Cerebras Systems Logo

Cerebras Systems

Platform Software Engineer - Cerebras AI Cloud

Posted 20 Hours Ago
Be an Early Applicant
2 Locations
Senior level
2 Locations
Senior level
As a Platform Software Engineer at Cerebras, you'll optimize their AI cloud platform for model training and inference, focusing on latency, load balancing, and system reliability. Responsibilities include defining production requirements, implementing scaling strategies, managing API servers, and resolving system bottlenecks.
The summary above was generated by AI

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 global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.

The Role

As a software engineer on our AI cloud platform, you will work on our cloud platform for AI model training and inference. In this role, you will be responsible for optimizing deployment for minimal latency and efficient load balancing, and on ensuring high reliability, scalability, security, and observability of our distributed training and inference infrastructure. You will define and document production requirements, implement scaling strategies, and ensure robust API server management and high availability. 

You will develop tools to map out system bottlenecks and sources of instability, and design and build solutions to address them. 

We're looking for talented software engineers who thrive in ambiguity, view change as an opportunity, and have a voracious desire to learn and share knowledge clearly and concisely. 

Skills & Qualifications   

  • 5+ years as an individual contributor developing production-grade cloud services.
  • Experience building ML serving and/or training services, preferably for modern generative AI models. 
  • Experience building high-reliability, production-grade cloud services.
  • Familiarity with the latest AI model architectures and efficient implementation of serving systems for these models. 
  • Strong problem-solving skills and the ability to thrive in ambiguous, rapidly changing conditions. 
  • Excellent communication skills and a passion for continuous learning and knowledge sharing. 

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 posts: Five Reasons to Join Cerebras in 2024 and Introducing Cerebras Inference: AI at Instant Speed

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.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Top Skills

Cloud Services
Machine Learning

Cerebras Systems Toronto, Ontario, CAN Office

150 King St W, Toronto, Ontario, Canada, M5H 1J9

Similar Jobs

Be an Early Applicant
4 Hours Ago
Toronto, ON, CAN
20,000 Employees
Senior level
20,000 Employees
Senior level
Food • Retail • Agriculture • Manufacturing
The OT Solution Architect will design and implement architectural solutions for OT systems, integrating them with cloud platforms while ensuring performance, security, and compliance. Responsibilities include optimizing system performance, collaborating with cross-functional teams, managing vendor relationships, and providing troubleshooting expertise.
Be an Early Applicant
4 Hours Ago
Toronto, ON, CAN
20,000 Employees
Expert/Leader
20,000 Employees
Expert/Leader
Food • Retail • Agriculture • Manufacturing
The Director of Data Platform Governance will lead the development and implementation of a governance strategy for Enterprise data assets, ensuring data quality, privacy, and security. The role involves collaborating with cross-functional teams to drive data governance solutions across McCain's business units and establish metrics for data quality. Additionally, the Director will oversee compliance with relevant regulations and establish frameworks for AI governance.
Be an Early Applicant
4 Hours Ago
Toronto, ON, CAN
20,000 Employees
Senior level
20,000 Employees
Senior level
Food • Retail • Agriculture • Manufacturing
The Sr Engineering Manager, SRE & Observability will lead the design, implementation, and monitoring of secure, fault-tolerant SRE and Observability infrastructure. Responsibilities include developing strategies, collaborating with teams, mentoring engineers, and driving operational excellence through advanced monitoring and automation techniques.

What you need to know about the Toronto Tech Scene

Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account