Postuler

Publié il y a 10 mois

ML Systems Performance Engineer

@ Cerebras Systems

Canada

Temps plein3+ ans d’expérience
Postuler
SIGNAUX

En bref

Cerebras Systems is hiring an ML Systems Performance Engineer on its inference performance team to drive end-to-end model inference speed and throughput. The work spans kernel performance debugging, system-level analysis, performance modeling and building performance visualization tools.

Responsabilités :

  • Build kernel-level and end-to-end performance models
  • Optimize kernel microcode and compiler algorithms for inference
  • Debug runtime performance on systems and clusters
  • Develop tools to visualize performance data

Résumé des exigences :

  • Bachelor's, Master's or PhD in EE or CS
  • Strong computer architecture background
  • 3+ years in CPU/GPU performance or kernel optimization
  • Experience with CPU/GPU simulators
  • Comfort with C++ and Python

Outils et compétences

Source et dates

Site carrière / système de candidatures · ashby

Date publiée par l’employeur
2026-01-21
Première détection par notre source
2026-10-08
Mise à jour du dossier source
2026-10-09

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauIntermédiaire
DomaineDéveloppement logiciel
Expérience3 an(s) et plus
Heures par semaine40 (estimé)
Milieu de travailBureau, Laboratoire
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
FormationBaccalauréat (exigé), Maîtrise (préféré), Doctorat (préféré)
Domaines d’étudesElectrical Engineering, Computer Science

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

Cerebras Systems

Profil d’entreprise sauvegardé

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The World's Fastest AI Inference

Description complète de l’entreprise

Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up. Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the largest AI supercomputers on Earth, while abstracting away the complexity of traditional distributed computing. From sub-second inference speeds to breakthrough training performance, Cerebras makes it easier to build and deploy state-of-the-art AI—from proprietary enterprise models to open-source projects downloaded millions of times. Here’s what makes our platform different: 🔦 Sub-second reasoning – Instant intelligence and real-time responsiveness, even at massive scale ⚡ Blazing-fast inference – Up to 100x performance gains over traditional AI infrastructure 🧠 Agentic AI in action – Models that can plan, act, and adapt autonomously 🌍 Scalable infrastructure – Built to move from prototype to global deployment without friction Cerebras solutions are available in the Cerebras Cloud or on-prem, serving leading enterprises, research labs, and government agencies worldwide. 👉 Learn more: www.cerebras.ai Join us: https://cerebras.net/careers/

Abonnés LinkedIn
119 613
Personnes associées sur LinkedIn
970
Bureaux déclarés
  • 1237 E Arques Ave, Sunnyvale, California 94085, US
  • 150 King St W, Toronto, Ontario M5H 1J9, CA
  • Tokyo, JP
  • Bangalore, IN
Catégories d’activité
  • Semiconductor
  • Artificial Intelligence
  • Software
  • Hardware
  • RISC
  • Artificial Intelligence (AI)
  • AI Infrastructure
  • Computer
Autres noms enregistrés
  • Cerebras Systems
  • Cerebras
Spécialités
  • artificial intelligence
  • deep learning
  • natural language processing
  • inference
  • machine learning
  • llm
  • AI
  • enterprise AI
  • and fast inference
Le profil indique une agence de recrutement
Non
Investissement total déclaré
4 674 771 259

La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.

Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up. Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the…

ChampValeur
SecteurSemiconductor Manufacturing
Taille501-1,000 employees
Siège socialSunnyvale, California
Type d’organisationPrivately Held
Spécialitésartificial intelligencedeep learningnatural language processinginferencemachine learningllmAIenterprise AIand fast inference
Offres sur Jobsy41
LinkedInVoir la page
Description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; 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.

Cerebras works with the leading 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.

About The Role

Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.

Responsibilities

  • Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.

  • Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.

  • Debug and understand runtime performance on the system and cluster.

  • Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.

Requirements

  • Bachelors / Masters / PhD in Electrical Engineering or Computer Science.

  • Strong background in computer architecture.

  • Exposure to and understanding of low-level deep learning / LLM math.

  • Strong analytical and problem-solving mindset.

  • 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).

  • Experience working on CPU/GPU simulators.

  • Exposure to performance profiling and debug on any system pipeline.

  • Comfort with C++ and Python.

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.

Find out more about what it's like to work at Cerebras here!

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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