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Baseten · San Francisco, CA · posted 35 days ago
By AtiveSite · Published 07/11/2026 · Updated 09/11/2026 · Every figure is linked to its source below.
| Employer | Baseten |
|---|---|
| Location | San Francisco, California |
| Field | Technology › Software engineering |
| Level | not stated |
| Source category | EPD, Inference |
| Posted | 2026-10-05 (35 days ago) |
| Work arrangement | A remote or flexible location is listed |
| Pay | Not published in the source listing |
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
THE ROLE
We're looking for inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference.
EXAMPLE INITIATIVES
You'll get to work on these types of projects as an Inference Performance engineer:
Agentic Kernels in Production
How we built the new fastest API for GLM-5.2
Live draft model training for speculative decoding
Making Kimi K3 Tokenization 18x faster
The Baseten Inference Stack
Driving model performance optimization
RESPONSIBILITIES
Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms.
Profile and optimize inference end to end, from kernel launch overhead and memory layout up to request scheduling, prefill/decode disaggregation, and cache-aware routing. Run cross-layer investigations, such as tracing a tail-latency regression from request timing through routing and batching down to a kernel.
Turn performance into cost savings. Improve tokens per GPU-hour, raise utilization, and give customers and internal teams clear latency/throughput/cost tradeoffs.
Bring up and tune new model architectures on new hardware quickly, often in the same week they're released.
Build benchmarking frameworks that measure real-world performance across model architectures, batch sizes, sequence lengths, and hardware configurations.
Contribute upstream to open-source inference engines (vLLM, SGLang, TensorRT-LLM), and partner closely with model, infrastructure, and customer-facing teams to ship wins.
REQUIREMENTS
Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field.
Experience with one or more general-purpose programming languages, such as Python or C++.
Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching).
Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM.
Demonstrated interest and experience in LLMs.
Deep understanding of GPU architecture.
NICE TO HAVE
Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs)
Contributed to vLLM, SGLang, TensorRT-LLM, or another inference engine.
Worked on large-scale distributed serving: autoscaling, load balancing, multi-region or multi-cloud capacity.
Written or optimized GPU kernels (CUDA, Triton, CUTLASS, or similar)
Worked on quantization (FP8/FP4, AWQ, GPTQ) or speculative decoding in production.
Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions.
BENEFITS
Competitive compensation, including meaningful equity
(U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Fertility and family-building stipend through Carrot
(U.S. only) Company-facilitated 401(k)
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Field: Technology Sub-niche: Software engineering All jobs at Baseten Jobs in California Jobs in San Francisco, CA San Francisco city guide California state guide San Francisco County economy
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This is a — role in the Technology field (Software engineering) at Baseten.
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 San Francisco, CA. Below is what the official statistics say about living and working there.
How San Francisco compares. Among the 145 largest places in California, San Francisco is #4 by population, #139 for homeownership (#1 = highest), #20 for remote work (#1 = most), #25 for college degrees (#1 = most). Its county, San Francisco County, is #3 of 58 counties for average pay ($174,103).
San Francisco has 830,235 residents (ACS 2020–2024), about 2.1% of the population of California. It covers 47 square miles of land, which works out to roughly 17,784 people per square mile. The median age is 40.0, 6% older than the state median (40.0 against 37.9).
The median gross rent is $2,476 a month (rent plus utilities), 22% above the state median ($2,476 against $2,036). Over a year that is 21.1% 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 $1,394,500, which is 9.9 times the median household income ($140,970); a ratio above 5 usually means buying is out of reach without savings or a second income. 38.2% of households own their home, 32% below the state average (38.2% against 55.9%). A low ownership share points to a rental-heavy market with more apartments and shorter stays.
The San Francisco-Oakland-Fremont, CA metropolitan area has 2,373,920 jobs in the BLS wage survey, and the median pay across all occupations is $74,260 a year, 46% above the national median ($74,260 against $50,980). The biggest occupation groups are office and administrative support (226,320 jobs, median $62,120); management (223,100 jobs, median $176,340); business and financial operations (207,030 jobs, median $112,960). The area is most specialised in computer and mathematical (1.9 times) and life, physical, and social science (1.8 times), where the share of workers is well above the national share. The best-paying groups with at least 5,000 jobs are management ($176,340) and computer and mathematical ($167,770). In 2026M09 the unemployment rate of San Francisco County was 4.0%. 69.6% of residents aged 16 and over are in the labour force. The city lies in San Francisco County; its jobs, pay by industry and GDP are on the county page.
Among workers, 28.6% drive alone, 18.7% use public transit, 9.3% walk, 31.0% work from home. 21.6% of workers commute 45 minutes or more, 11% above the state average (21.6% 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.
60.3% of adults aged 25 and over hold a bachelor's degree or higher, 63% above the state share (60.3% against 37.1%). 34.0% of residents were born outside the United States, 26% above the state share (34.0% against 27.0%). The poverty rate is 11.2%, 7% below the state rate (11.2% against 12.0%).
The warmest month is Sep, averaging 59°F (14.9°C), and the coolest is Apr at 53°F (11.6°C). About 515 mm (20 inches) of precipitation falls in a year; Dec is the wettest month (112 mm) and Jul the driest (2 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: Daly City (31 miles, rent 3% higher); Pacifica (31 miles, rent 25% higher); San Bruno (34 miles, rent 12% higher); Millbrae (36 miles, rent 32% higher). Rent differences are against San Francisco; use the Compare tab to put any two cities side by side.
Full guide to San Francisco →California guideAll jobs in San Francisco
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Places within 50 miles (straight line) of San Francisco, 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 ⇅ |
|---|---|---|---|---|---|---|---|
| San Francisco, CA | 0 mi | $2,476 | $1,394,500 | $140,970 | 21.6% | n/a | Jobs |
| Daly City, CA | 31 mi | $2,551 | $1,115,000 | $123,547 | 19.6% | n/a | Jobs |
| Pacifica, CA | 31 mi | $3,098 | $1,249,800 | $160,523 | 15.5% | n/a | — |
| San Bruno, CA | 34 mi | $2,773 | $1,207,500 | $141,272 | 12.2% | n/a | — |
| Millbrae, CA | 36 mi | $3,272 | $1,934,900 | $163,476 | 21.8% | n/a | Jobs |
| Brisbane, CA | 36 mi | $2,574 | $1,232,200 | $156,169 | 29.8% | n/a | Jobs |
| South San Francisco, CA | 36 mi | $2,802 | $1,188,800 | $136,578 | 15.2% | n/a | Jobs |
| Half Moon Bay, CA | 37 mi | $2,433 | $1,549,500 | $157,884 | 26.7% | n/a | — |
| Burlingame, CA | 38 mi | $2,785 | $2,000,001 | $174,000 | 23.1% | n/a | Jobs |
| Richmond, CA | 40 mi | $1,960 | $668,200 | $95,391 | 28.8% | n/a | — |
| San Mateo, CA | 41 mi | $3,077 | $1,618,700 | $153,504 | 15.8% | n/a | Jobs |
| Berkeley, CA | 41 mi | $2,133 | $1,413,900 | $108,092 | 20.8% | n/a | Jobs |
| Alameda, CA | 42 mi | $2,474 | $1,235,700 | $137,697 | 27.3% | n/a | Jobs |
| Belmont, CA | 43 mi | $2,875 | $2,000,001 | $205,297 | 18.6% | n/a | Jobs |
| Oakland, CA | 44 mi | $1,979 | $929,900 | $101,600 | 21.9% | n/a | Jobs |
| Foster City, CA | 44 mi | $3,501 | $1,838,200 | $199,143 | 20.6% | n/a | Jobs |
| San Carlos, CA | 45 mi | $2,854 | $2,000,001 | $237,470 | 14.9% | n/a | Jobs |
| Redwood City, CA | 47 mi | $2,968 | $1,801,700 | $157,814 | 10.2% | n/a | Jobs |
| San Leandro, CA | 48 mi | $2,186 | $844,200 | $101,420 | 23.7% | n/a | — |
| Atherton, CA | 49 mi | $3,501 | $2,000,001 | $250,001 | 7.0% | n/a | — |
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 San Francisco, 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 Francisco, CA | 0 mi | 830,235 |
| San Jose, CA | 73 mi | 990,138 |
| Los Angeles, CA | 364 mi | 3,857,263 |
| San Diego, CA | 475 mi | 1,389,526 |
| Phoenix, AZ | 678 mi | 1,642,323 |
| Seattle, WA | 684 mi | 754,195 |
| Denver, CO | 986 mi | 718,877 |
| Oklahoma City, OK | 1,420 mi | 697,125 |
| Fort Worth, TX | 1,484 mi | 963,194 |
| Dallas, TX | 1,515 mi | 1,307,930 |
| San Antonio, TX | 1,516 mi | 1,479,835 |
| Austin, TX | 1,530 mi | 979,539 |
| Houston, TX | 1,673 mi | 2,328,253 |
| Chicago, IL | 1,885 mi | 2,711,226 |
| Indianapolis, IN | 1,979 mi | 885,860 |
| Columbus, OH | 2,142 mi | 914,802 |
| Charlotte, NC | 2,332 mi | 903,844 |
| Jacksonville, FL | 2,403 mi | 977,670 |
| Philadelphia, PA | 2,550 mi | 1,579,706 |
| New York, NY | 2,602 mi | 8,483,844 |
| City ⇅ | Straight-line distance ⇅ | Open jobs ⇅ |
|---|---|---|
| Alameda, CA | 42 mi | 38 |
| Belmont, CA | 43 mi | 2 |
| Redwood City, CA | 47 mi | 48 |
| Palo Alto, CA | 54 mi | 332 |
| Sunnyvale, CA | 60 mi | 185 |
| Fremont, CA | 62 mi | 9 |
| Pleasanton, CA | 63 mi | 6 |
| Milpitas, CA | 66 mi | 15 |
| Campbell, CA | 67 mi | 7 |
| San Jose, CA | 73 mi | 899 |
| Capitola, CA | 79 mi | 1 |
| Sacramento, CA | 103 mi | 56 |
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A private-sector role in technology (software engineering) listed 35 days ago. The full description is on this page and on the employer's page.
San Francisco, CA. A remote or flexible location is listed; confirm with the employer which states are accepted.
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 San Francisco is $2,476 a month and median household income $140,970 (ACS 2020–2024).
It was posted on 2026-10-05 (35 days ago). Jobs older than 90 days are not shown.
Yes: browse software engineering jobs in California.
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