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ML API Features SDET

Cerebras

ML API Features SDET

Cerebras

Sunnyvale CA or Toronto Canada

·

On-site

·

Full-time

·

2w ago

Required Skills

Python

C++

Go

Test Automation

Debugging

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 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.

Responsibilities

  • Understand new features end-to-end, and develop tests and tools to ensure quality.

  • Contribute to industry standard benchmarks.

  • Drive automation to improve internal efficiency.

  • Understand trade off between coverage and resource requirements.

  • Work in a highly agile environment where priorities change frequently.

  • Effectively communicate across teams and timezones.

Skills & Qualifications

  • 2+ years of relevant industry experience in Software integration, development or 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 distributed scale out deployment.

  • Experience working effectively across teams, including product development, product management, customer operations, and field teams.

  • Excellent verbal and written communication skills.

  • Strong organizational skills, teamwork, and can-do attitude.

  • Experience working with geographically dispersed teams across time zones.

Preferred Skills & Qualifications

  • Experience in working with ML workloads such as LLM/Multimodal training or inference.

  • Experience with hardware architecture, performance optimizations, compilers and ML frameworks.

  • Experience working with distributed systems, cloud and security.

  • Experience working with microservices deployment, debugging and orchestration.

Location

  • This role follows a hybrid schedule, requiring in-office presence 3 days per week. Please note, fully remote is not an option.

  • Office locations: Sunnyvale CA, Toronto, Canada.

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:

  • 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.

Read our blog: Five Reasons to Join Cerebras in 2026.

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.

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About Cerebras

Cerebras

Cerebras

Series F+

Cerebras Systems Inc. is an American artificial intelligence (AI) company with offices in Sunnyvale, San Diego, Toronto, and Bangalore, India. Cerebras builds computer systems for complex AI deep learning applications.

201-500

Employees

Sunnyvale

Headquarters

$4.1B

Valuation

Reviews

4.1

39 reviews

Work Life Balance

3.3

Compensation

4.8

Culture

4.1

Career

4.4

Management

4.0

90%

Recommend to a Friend

Pros

Strong research and publication culture

Impact on the future of AI development

Brilliant colleagues passionate about the field

Cons

Work-life balance can suffer during critical periods

High expectations and pressure to deliver

Competition for resources and recognition

Salary Ranges

2 data points

L3

Intern

L3 · Compiler Engineer Intern

1 reports

$87,000

total / year

Base

$87,000

Stock

-

Bonus

-

$87,000

$87,000

Interview Experience

50 interviews

Difficulty

3.9

/ 5

Duration

21-35 weeks

Offer Rate

23%

Experience

Positive 72%

Neutral 9%

Negative 19%

Interview Process

1

Recruiter Screen

2

ML Coding

3

ML System Design

4

Research Discussion

5

Team Interviews

Common Questions

ML fundamentals

Design an ML system

Research paper discussion

Statistical concepts