Cerebras’ systems are designed with a singular focus on machine learning. Our processor is the Wafer Scale Engine (WSE), a single chip with performance equivalent to a cluster of GPUs, giving the user cluster-scale capability with the simplicity of programming a single device. Because of this programming simplicity, large model training can be scaled out using simple data parallelism to the performance of thousands of GPUs. ML practitioners can focus on their machine learning, rather than parallelizing and distributing their applications across many devices. The Cerebras hardware architecture is designed with unique capabilities including orders of magnitude higher memory bandwidth and unstructured sparsity acceleration, not accessible on traditional GPUs. With a rare combination of cutting-edge hardware and deep expertise in machine learning, we stand among the select few global organizations capable of conducting large-scale innovative deep learning research and developing novel ML algorithms not possible on traditional hardware.

About the role

We are looking for a senior machine learning engineer who can work with a team of talented engineers to develop innovative machine learning solutions based on our wafer scale engine. You will be responsible for designing, implementing, and optimizing large-scale machine learning models, as well as conducting performance analysis and troubleshooting. You will also collaborate with other teams to integrate machine learning capabilities into our products and services.

Responsibilities

• Provide technical guidance and direction to a team of machine learning engineers working on various machine learning projects
• Design and implement scalable and efficient machine learning systems using our wafer scale engine, especially
• Perform pre-train and fine-tune trillion parameter level LLMs on the wafer scale engine clusters, with hyper-parameter tuning, model selection, and evaluation using appropriate metrics and tools
• Research and apply the latest advancements in machine learning and deep learning to improve our solutions
• Collaborate with other teams to integrate machine learning features into our products and service

Requirements

• Master’s or PhD degree in computer science, engineering, mathematics, or related field
• 5+ years of experience in machine learning, data science, or software engineering
• Proficient in Python, PyTorch, or other machine learning frameworks and libraries
• Experience in developing and deploying large-scale machine learning models using distributed systems and cloud platforms
• Experience in applying machine learning techniques to various domains such as computer vision, natural language processing, recommender systems, etc.
• Experience in leading and mentoring machine learning engineers or data scientists
• Strong knowledge of machine learning theory, algorithms, and best practices
• Ability to work independently and collaboratively with cross-functional teams
• Excellent communication, presentation, and problem-solving skills

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.

Apply today and become part of the forefront of groundbreaking advancements in AI.