Strategic Sourcing Manager, Data Center Infrastructure, Electrical & Mechanical
OpenAI · San Francisco, CA · Cloud, IT and infrastructure · posted today
OpenAI · San Francisco, CA · posted 88 days ago
By AtiveSite · Published 07/11/2026 · Updated 09/11/2026 · Every figure is linked to its source below.
| Employer | OpenAI |
|---|---|
| Location | San Francisco, California |
| Field | Technology › Data, analytics and AI |
| Level | not stated |
| Source category | Core Product & Platform, Core Product & Platform | API |
| Posted | 2026-08-13 (88 days ago) |
| Work arrangement | On-site at the location listed |
| Pay | Not published in the source listing |
OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS. The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied.
The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure.
We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration.
You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time.
Partner with strategic customers and internal teams to define target model behaviors, diagnose failure modes, and translate real-world needs into training, evaluation, and system requirements.
Build and scale production ML systems for model customization, post-training, and fine-tuning-as-a-service workflows.
Design, run, and interpret experiments to see whether training and customization workflows are producing the intended outcomes, and identify changes to data, evaluation, training, or infrastructure that improve performance.
Partner with backend and infrastructure engineers to integrate ML capabilities into AWS-native API environments.
Feed learnings from partner deployments back into the platform by proposing and implementing improvements to post-training systems, tooling, APIs, and developer workflows.
Work closely with Research and Applied teams to bring model improvements, training workflows, and evaluation best practices into production.
Help design systems that allow strategic partners and enterprise customers to safely customize OpenAI models for high-value use cases.
Debug and improve complex systems spanning model behavior, training data, APIs, distributed infrastructure, and customer-facing product surfaces.
Operate with high ownership in a 0→1 environment where requirements are ambiguous, systems are evolving quickly, and reliability matters.
Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
3+ years of professional engineering experience in relevant ML, infrastructure, or product-driven engineering roles.
Strong ML engineering experience building, training, fine-tuning, evaluating, or deploying production AI systems, with hands-on experience in deep learning, transformer models, and frameworks like PyTorch or TensorFlow.
Hands-on experience with training and fine-tuning large language models, including methods like supervised fine-tuning, distillation, preference optimization, reinforcement learning, or other post-training techniques.
Strong software engineering fundamentals, including data structures, algorithms, systems design, and high-quality production code in Python, Rust, or similar languages.
Experience with model customization, evaluation systems, data pipelines, distributed systems, cloud infrastructure, or production ML platform tradeoffs.
Ability to operate across model behavior, APIs, and infrastructure, while collaborating closely with Research, Safety, product engineering, infrastructure, and external technical partners.
Comfort moving quickly through ambiguity, owning problems end-to-end, and learning whatever is needed to get the job done.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Field: Technology Sub-niche: Data, analytics and AI All jobs at OpenAI 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 (Data, analytics and AI) at OpenAI.
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 | — |
| 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 (713) Software engineering (4089) Cloud, IT and infrastructure (1040) Product management (836)
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 | 45 |
| Palo Alto, CA | 54 mi | 298 |
| Sunnyvale, CA | 60 mi | 83 |
| Fremont, CA | 62 mi | 6 |
| Pleasanton, CA | 63 mi | 6 |
| Milpitas, CA | 66 mi | 2 |
| Campbell, CA | 67 mi | 7 |
| San Jose, CA | 73 mi | 698 |
| Capitola, CA | 79 mi | 1 |
| Sacramento, CA | 103 mi | 53 |
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A private-sector role in technology (data, analytics and ai) listed 88 days ago. The full description is on this page and on the employer's page.
San Francisco, CA.
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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 2026-08-13 (88 days ago). Jobs older than 90 days are not shown.
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