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Cerebras · Sunnyvale, CA · posted 349 days ago
By AtiveSite · Published 07/11/2026 · Updated 09/11/2026 · Every figure is linked to its source below.
| Employer | Cerebras |
|---|---|
| Location | Sunnyvale, California |
| Field | Technology › Software engineering |
| Level | not stated |
| Source category | Software Engineering , Inference Service |
| Posted | 2025-11-25 (349 days ago) |
| Work arrangement | On-site at the location listed |
| Pay | Not published in the source listing |
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.
Cerebras is building a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.
We are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant.
You will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers.
Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure.
Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible.
Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack.
Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads.
Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication.
Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware.
Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases.
Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems.
5+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems.
Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads.
Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software.
Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system.
Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology.
Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box.
Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production.
Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements.
Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.
Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools.
Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms.
Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project.
Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures.
Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control.
Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling.
Experience optimizing Mixture-of-Experts or multimodal models.
Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap.
Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects.
Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems.
Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities.
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.
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.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
Field: Technology Sub-niche: Software engineering All jobs at Cerebras Jobs in California Jobs in Sunnyvale, CA Sunnyvale city guide California state guide Santa Clara County economy
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This is a — role in the Technology field (Software engineering) at Cerebras.
We could not match this job title to one occupation in the official wage statistics, so no pay estimate is shown. Pay is not in the source listing; ask the employer for the range and compare in the 240 job niches.
Estimate for a wage earner: 2026 federal brackets and standard deduction (IRS), Social Security 6.2% up to $184,500, Medicare 1.45% (+0.9% above $200,000 single / $250,000 married), and a state rate you set; set your own state tax rate. It ignores credits, pre-tax deductions, local taxes and benefits. Sources: IRS: tax year 2026 inflation adjustments · SSA wage base per Federal Register notice 2025-19763.
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The job is in Sunnyvale, CA. Below is what the official statistics say about living and working there.
How Sunnyvale compares. Among the 145 largest places in California, Sunnyvale is #37 by population, #12 for long commutes (#1 = fewest), #15 for household income (#1 = highest), #129 for rent (#1 = cheapest). Its county, Santa Clara County, is #1 of 58 counties for average pay ($197,043).
Sunnyvale has 154,236 residents (ACS 2020–2024), about 0.4% of the population of California. It covers 22 square miles of land, which works out to roughly 6,992 people per square mile. The median age is 35.2, 7% younger than the state median (35.2 against 37.9).
The median gross rent is $3,039 a month (rent plus utilities), 49% above the state median ($3,039 against $2,036). Over a year that is 19.6% of the median household income. US housing guidance treats housing as affordable when it takes 30% of income or less, so the typical household is under that line. The median home value is $1,801,800, which is 9.7 times the median household income ($186,170); a ratio above 5 usually means buying is out of reach without savings or a second income. 43.8% of households own their home, 22% below the state average (43.8% against 55.9%). A low ownership share points to a rental-heavy market with more apartments and shorter stays.
The San Jose-Sunnyvale-Santa Clara, CA metropolitan area has 1,134,970 jobs in the BLS wage survey, and the median pay across all occupations is $84,050 a year, 65% above the national median ($84,050 against $50,980). The biggest occupation groups are computer and mathematical (149,970 jobs, median $186,320); management (115,110 jobs, median $210,750); business and financial operations (94,210 jobs, median $125,240). The area is most specialised in computer and mathematical (3.9 times) and architecture and engineering (2.5 times), where the share of workers is well above the national share. The best-paying groups with at least 5,000 jobs are management ($210,750) and legal ($195,190). In 2026M09 the unemployment rate of Santa Clara County was 4.2%. 72.4% of residents aged 16 and over are in the labour force. The city lies in Santa Clara County; its jobs, pay by industry and GDP are on the county page.
Among workers, 53.7% drive alone, 4.0% use public transit, 1.6% walk, 29.2% work from home. 9.0% of workers commute 45 minutes or more, 54% below the state average (9.0% against 19.4%). Remote work is more common than in the state as a whole, which widens the set of employers a resident can work for without moving.
69.3% of adults aged 25 and over hold a bachelor's degree or higher, 87% above the state share (69.3% against 37.1%). 50.2% of residents were born outside the United States, 86% above the state share (50.2% against 27.0%). The poverty rate is 5.8%, 52% below the state rate (5.8% against 12.0%).
The warmest month is Aug, averaging 68°F (19.8°C), and the coolest is Jan at 47°F (8.3°C). About 510 mm (20 inches) of precipitation falls in a year; Dec is the wettest month (114 mm) and Jul the driest (0 mm). These values come from NASA satellite-based climatology on a grid of about 50 km, so they describe the wider area, not a weather station in the city.
Closest cities in this guide: Mountain View (3 miles, similar rent); Santa Clara (4 miles, similar rent); Los Altos (4 miles, rent 15% higher); Cupertino (5 miles, rent 15% higher). Rent differences are against Sunnyvale; use the Compare tab to put any two cities side by side.
Full guide to Sunnyvale →California guideAll jobs in Sunnyvale
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Places within 50 miles (straight line) of Sunnyvale, CA that have a guide, with what living there costs. No pay estimate is shown because the title did not match one occupation.
| Place ⇅ | Distance from the job city ⇅ | Median rent ⇅ | Median home value ⇅ | Median household income ⇅ | Commute 45+ min ⇅ | Rent as % of occupation pay ⇅ | Open jobs there ⇅ |
|---|---|---|---|---|---|---|---|
| Sunnyvale, CA | 0 mi | $3,039 | $1,801,800 | $186,170 | 9.0% | n/a | Jobs |
| Mountain View, CA | 3 mi | $3,062 | $1,927,000 | $189,917 | 9.3% | n/a | Jobs |
| Santa Clara, CA | 4 mi | $3,016 | $1,582,600 | $178,958 | 8.9% | n/a | Jobs |
| Los Altos, CA | 4 mi | $3,501 | $2,000,001 | $250,001 | 8.3% | n/a | — |
| Cupertino, CA | 5 mi | $3,501 | $2,000,001 | $234,707 | 9.1% | n/a | Jobs |
| Los Altos Hills, CA | 6 mi | $3,501 | $2,000,001 | $250,001 | 18.0% | n/a | — |
| Palo Alto, CA | 6 mi | $3,484 | $2,000,001 | $231,101 | 8.2% | n/a | Jobs |
| Saratoga, CA | 8 mi | $3,501 | $2,000,001 | $250,001 | 8.3% | n/a | — |
| Milpitas, CA | 8 mi | $3,120 | $1,251,700 | $178,798 | 15.2% | n/a | Jobs |
| East Palo Alto, CA | 8 mi | $2,244 | $1,102,600 | $113,493 | 9.7% | n/a | — |
| Newark, CA | 8 mi | $2,776 | $1,142,800 | $169,064 | 22.2% | n/a | Jobs |
| Campbell, CA | 8 mi | $2,737 | $1,617,000 | $145,268 | 10.4% | n/a | Jobs |
| Fremont, CA | 9 mi | $2,933 | $1,403,800 | $181,506 | 23.6% | n/a | Jobs |
| Menlo Park, CA | 9 mi | $3,239 | $2,000,001 | $210,025 | 11.5% | n/a | Jobs |
| Atherton, CA | 11 mi | $3,501 | $2,000,001 | $250,001 | 7.0% | n/a | — |
| Los Gatos, CA | 11 mi | $3,247 | $2,000,001 | $217,554 | 17.6% | n/a | — |
| San Jose, CA | 13 mi | $2,669 | $1,233,200 | $146,427 | 15.3% | n/a | Jobs |
| Redwood City, CA | 14 mi | $2,968 | $1,801,700 | $157,814 | 10.2% | n/a | Jobs |
| Union City, CA | 15 mi | $2,713 | $1,104,900 | $133,715 | 24.0% | n/a | — |
| San Carlos, CA | 15 mi | $2,854 | $2,000,001 | $237,470 | 14.9% | n/a | Jobs |
We could not match this title to one occupation, so here are the other sub-niches in Technology, where your skills may carry over:
Cybersecurity (762) Data, analytics and AI (3719) Cloud, IT and infrastructure (1147) Product management (927)
How far Sunnyvale, CA is from the 20 largest US cities, in straight-line miles (not driving distance). Click a column to sort.
| From ⇅ | Straight-line distance (miles) ⇅ | Population of that city ⇅ |
|---|---|---|
| San Jose, CA | 13 mi | 990,138 |
| San Francisco, CA | 60 mi | 830,235 |
| Los Angeles, CA | 309 mi | 3,857,263 |
| San Diego, CA | 420 mi | 1,389,526 |
| Phoenix, AZ | 618 mi | 1,642,323 |
| Seattle, WA | 707 mi | 754,195 |
| Denver, CO | 939 mi | 718,877 |
| Oklahoma City, OK | 1,365 mi | 697,125 |
| Fort Worth, TX | 1,427 mi | 963,194 |
| San Antonio, TX | 1,457 mi | 1,479,835 |
| Dallas, TX | 1,458 mi | 1,307,930 |
| Austin, TX | 1,471 mi | 979,539 |
| Houston, TX | 1,614 mi | 2,328,253 |
| Chicago, IL | 1,841 mi | 2,711,226 |
| Indianapolis, IN | 1,932 mi | 885,860 |
| Columbus, OH | 2,097 mi | 914,802 |
| Charlotte, NC | 2,281 mi | 903,844 |
| Jacksonville, FL | 2,348 mi | 977,670 |
| Philadelphia, PA | 2,506 mi | 1,579,706 |
| New York, NY | 2,559 mi | 8,483,844 |
| City ⇅ | Straight-line distance ⇅ | Open jobs ⇅ |
|---|---|---|
| Palo Alto, CA | 6 mi | 332 |
| Milpitas, CA | 8 mi | 15 |
| Campbell, CA | 8 mi | 7 |
| Fremont, CA | 9 mi | 9 |
| San Jose, CA | 13 mi | 899 |
| Redwood City, CA | 14 mi | 48 |
| Belmont, CA | 17 mi | 2 |
| Pleasanton, CA | 21 mi | 6 |
| Alameda, CA | 28 mi | 38 |
| Capitola, CA | 29 mi | 1 |
| San Francisco, CA | 60 mi | 3,359 |
| Sacramento, CA | 87 mi | 56 |
Cerebras is the employer in this listing. See all its open jobs here →
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A private-sector role in technology (software engineering) listed 349 days ago. The full description is on this page and on the employer's page.
Sunnyvale, CA.
Use the "View this job and apply on the employer's page" button. AtiveSite does not receive applications.
The listing does not publish pay, and we could not match the title to one official occupation.
Median rent in Sunnyvale is $3,039 a month and median household income $186,170 (ACS 2020–2024).
It was posted on 2025-11-25 (349 days ago). Jobs older than 90 days are not shown.
Yes: browse software engineering jobs in California.
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