Senior Performance Analyst, Inference
Cerebras Systems, Sunnyvale, CA, United States
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.
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 We are hiring aSeniorPerformanceAnalysttojoin our Product team.Youare an expert onstate-of-the-artinference performance andwill serve asour resident expert on how Cerebras stacks up againstalternative inference providerson both price and performance.This role sits at the intersection ofperformance benchmarkingfrom first principlesandcompetitive intelligence.The role has two core pillars:
Performance Benchmarking
You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This includes metrics like tokens per second, time to first token, latency under concurrency, and total cost of ownership (TCO).
Competitive Pricing Intelligence
You will build and maintain a living model of competitor pricing across the AI inference landscape, including cloud providers, custom silicon vendors, and inference API platforms. You will work directly with our Sales and Product teams to translate this intelligence into pricing recommendations for enterprise contracts, ensuring Cerebras offers a compelling value proposition for every customer.
This role requires deep, hands‑on fluency with open‑source inference stacks (vLLM,SGLang,TensorRT‑LLM), GPU kernel‑level optimization toolchains (CUDA, Triton), and an intuitive understanding of how transformer architecture decisions—attention mechanisms, model sizing, quantization, KV‑cache strategies—interact with the realities of GPU memory hierarchies and compute budgets.
Responsibilities
Design standardized benchmark suites for inference workloads (code generation, summarization, multi‑turn conversation, agentic tool use) that enable fair, reproducible comparisons.
Stay current with GPU optimization communities (CUDA, Triton,TensorRT) and evaluate how new kernel fusions, flash‑attention variants, and quantization techniques shift performance ceilings.
Build and continuously update a competitive pricing model covering token‑based pricing, throughput‑based pricing, and enterprise contract structures across major inference providers.
Monitor industry announcements, pricing changes, and new product launches. Synthesize findings into actionable briefs for the Sales and Product teams.
Partner with Sales to build deal‑specific competitive analyses showing total cost of ownership and performance advantages for enterprise prospects.
Collaborate with Product and Engineering to identify where competitors are closing gaps or where Cerebras has underappreciated advantages.
Track third‑party benchmarking sources (Artificial Analysis,InferenceX) and ensure Cerebras is well‑represented and accurately measured.
Skills & Qualifications Required
Deep practical experience with state‑of‑the‑art open‑source inference frameworks like vLLM,SGLang, or TensorRT‑LLM.
5+ years of experience in ML systems, ML research engineering, or high‑performance computing.
Strong understanding of LLM inference economics: tokens, throughput, latency, batch sizes, precision trade‑offs, and how these translate to customer cost.
Strong understanding of transformer model architecture internals such as attention mechanisms (MHA, MQA, GQA, MLA, DSA, MHA) and KV‑cache management, and how each affect memory and compute profiles.
Self‑directed and resourceful.
Preferred
Background in ML research (publications or significant open‑source contributions) with a system or efficiency focus.
Contributions to open‑source inference or kernel optimization projects.
Excellent communication skills. You will collaborate with executives, write for engineers, and create materials for sales leaders.
Why Join 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.
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.
As set forth in Cerebras Systems’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:
A 'disabled veteran' is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.
A 'recently separated veteran' means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.
An 'active duty wartime or campaign badge veteran' means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.
An 'Armed forces service medal veteran' means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.
Voluntary Self-Identification of Disability We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress toward this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years.
Alcohol or other substance use disorder (not currently using drugs illegally)
Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS
Blind or low vision
Cancer (past or present)
Cardiovascular or heart disease
Celiac disease
Cerebral palsy
Deaf or serious difficulty hearing
Diabetes
Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders
Epilepsy or other seizure disorder
Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome
Intellectual or developmental disability
Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD
Missing limbs or partially missing limbs
Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports
Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS)
Neurodivergence, for example, attention‑deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities
Partial or complete paralysis (any cause)
Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema
Short stature (dwarfism)
Traumatic brain injury
This website or its third‑party tools process personal data. For more details, click here to review our CCPA disclosure notice.
#J-18808-Ljbffr
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 We are hiring aSeniorPerformanceAnalysttojoin our Product team.Youare an expert onstate-of-the-artinference performance andwill serve asour resident expert on how Cerebras stacks up againstalternative inference providerson both price and performance.This role sits at the intersection ofperformance benchmarkingfrom first principlesandcompetitive intelligence.The role has two core pillars:
Performance Benchmarking
You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This includes metrics like tokens per second, time to first token, latency under concurrency, and total cost of ownership (TCO).
Competitive Pricing Intelligence
You will build and maintain a living model of competitor pricing across the AI inference landscape, including cloud providers, custom silicon vendors, and inference API platforms. You will work directly with our Sales and Product teams to translate this intelligence into pricing recommendations for enterprise contracts, ensuring Cerebras offers a compelling value proposition for every customer.
This role requires deep, hands‑on fluency with open‑source inference stacks (vLLM,SGLang,TensorRT‑LLM), GPU kernel‑level optimization toolchains (CUDA, Triton), and an intuitive understanding of how transformer architecture decisions—attention mechanisms, model sizing, quantization, KV‑cache strategies—interact with the realities of GPU memory hierarchies and compute budgets.
Responsibilities
Design standardized benchmark suites for inference workloads (code generation, summarization, multi‑turn conversation, agentic tool use) that enable fair, reproducible comparisons.
Stay current with GPU optimization communities (CUDA, Triton,TensorRT) and evaluate how new kernel fusions, flash‑attention variants, and quantization techniques shift performance ceilings.
Build and continuously update a competitive pricing model covering token‑based pricing, throughput‑based pricing, and enterprise contract structures across major inference providers.
Monitor industry announcements, pricing changes, and new product launches. Synthesize findings into actionable briefs for the Sales and Product teams.
Partner with Sales to build deal‑specific competitive analyses showing total cost of ownership and performance advantages for enterprise prospects.
Collaborate with Product and Engineering to identify where competitors are closing gaps or where Cerebras has underappreciated advantages.
Track third‑party benchmarking sources (Artificial Analysis,InferenceX) and ensure Cerebras is well‑represented and accurately measured.
Skills & Qualifications Required
Deep practical experience with state‑of‑the‑art open‑source inference frameworks like vLLM,SGLang, or TensorRT‑LLM.
5+ years of experience in ML systems, ML research engineering, or high‑performance computing.
Strong understanding of LLM inference economics: tokens, throughput, latency, batch sizes, precision trade‑offs, and how these translate to customer cost.
Strong understanding of transformer model architecture internals such as attention mechanisms (MHA, MQA, GQA, MLA, DSA, MHA) and KV‑cache management, and how each affect memory and compute profiles.
Self‑directed and resourceful.
Preferred
Background in ML research (publications or significant open‑source contributions) with a system or efficiency focus.
Contributions to open‑source inference or kernel optimization projects.
Excellent communication skills. You will collaborate with executives, write for engineers, and create materials for sales leaders.
Why Join 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.
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.
As set forth in Cerebras Systems’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:
A 'disabled veteran' is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.
A 'recently separated veteran' means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.
An 'active duty wartime or campaign badge veteran' means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.
An 'Armed forces service medal veteran' means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.
Voluntary Self-Identification of Disability We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress toward this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years.
Alcohol or other substance use disorder (not currently using drugs illegally)
Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS
Blind or low vision
Cancer (past or present)
Cardiovascular or heart disease
Celiac disease
Cerebral palsy
Deaf or serious difficulty hearing
Diabetes
Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders
Epilepsy or other seizure disorder
Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome
Intellectual or developmental disability
Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD
Missing limbs or partially missing limbs
Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports
Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS)
Neurodivergence, for example, attention‑deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities
Partial or complete paralysis (any cause)
Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema
Short stature (dwarfism)
Traumatic brain injury
This website or its third‑party tools process personal data. For more details, click here to review our CCPA disclosure notice.
#J-18808-Ljbffr