Strategic Sourcing Manager, Data Center Infrastructure, Electrical & Mechanical
OpenAI · San Francisco, CA · Cloud, IT and infrastructure · posted today
OpenAI · Seattle, WA · posted 46 days ago
By AtiveSite · Published 07/11/2026 · Updated 09/11/2026 · Every figure is linked to its source below.
| Employer | OpenAI |
|---|---|
| Location | Seattle, Washington |
| Field | Technology › Data, analytics and AI |
| Level | not stated |
| Source category | Applied AI, Applied AI Engineering |
| Posted | 2026-09-24 (46 days ago) |
| Work arrangement | A remote or flexible location is listed |
| Pay | Not published in the source listing |
The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions.
Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship.
Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence.
We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely.
We are evolving experimentation systems to help teams learn from product behavior and make better evidence-based decisions.
Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use.
We are looking for a Machine Learning Engineer to lead the technical direction for ML-powered experimentation and insights capabilities. You will build production systems that learn from privacy-protected product and experimentation data to generate evidence-backed insights and support decision-making, and help teams decide which ideas are worth testing live.
This is an end-to-end, 0-to-1 role. You will work across ML modeling, retrieval and LLM systems, statistical methods, simulation, data and training pipelines, backend services, and user- and agent-facing product experiences. The hard part is not merely producing a plausible answer. It is making each insight and prediction traceable, calibrated, useful, and safe enough to influence real product decisions.
Live experiments remain the source of causal validation. You will design systems that make uncertainty explicit, backtest against historical outcomes, compare predictions with online results, learn from misses, and abstain when the evidence is weak. You will preserve clear review, permission, and approval boundaries as automation becomes more powerful.
You will collaborate closely with teams building ChatGPT, Codex, model measurement workflows, consumer products, Growth, business subscription experiences, developer products, and shared infrastructure. You will turn their most important learning and decision problems into general platform capabilities that can support the full company.
Set and execute the technical roadmap for Generative Insights and Predictive Experimentation, from early prototypes through production adoption.
Build cross-experiment learning systems that retrieve and synthesize historical experiments, detect recurring effects and segment behavior, reanalyze prior results when data or methods improve, and generate hypotheses with clear evidence and provenance.
Develop predictive models and simulation workflows, including simulation-based evaluation approaches, to estimate likely impact, affected segments, regression risk, and uncertainty before a full live experiment.
Create high-quality datasets and feature or retrieval pipelines from exposures, events, metrics, experiment metadata, and replay data, with strong lineage, freshness, privacy, and data-quality controls.
Establish rigorous evaluation through offline benchmarks, backtests, calibration, drift monitoring, prediction-to-outcome comparisons, and explicit failure or abstention behavior.
Turn models into durable product, API, and agent workflows that move from an insight to experiment design, approval-gated action, and measured learning.
Partner deeply with data science and product teams on experiment design, causal inference, sequential decision-making, variance reduction, and the boundary between prediction and causal evidence.
Build reliable services and intuitive workflows so sophisticated ML capabilities are understandable and useful to teams making high-stakes product decisions.
Provide technical leadership across engineering, product, data science, and research partners, and raise the bar for production ML quality across the platform.
Have led ambiguous 0-to-1 production ML products where success was measured by better real-world decisions, not only offline model metrics.
Have strong hands-on experience across the ML lifecycle: dataset design, training or adaptation, evaluation, deployment, monitoring, and iteration.
Bring depth in one or more of LLM and retrieval systems, ranking or recommendation, forecasting or anomaly detection, causal ML or experiment analysis, or simulation. You do not need to have done all of them.
Have strong software engineering fundamentals and can build high-quality production systems in Python while working comfortably across data, backend, and platform boundaries.
Have a strong grounding in machine learning, statistics, computer science, or a related field through formal study or equivalent practical experience.
Understand experimentation and statistical reasoning, especially why predictive accuracy is not the same as causal validity.
Treat calibration, uncertainty, provenance, privacy, and human review as product requirements, not cleanup work.
Can translate ambiguous partner questions into a product and technical roadmap, and work well with product, data science, research, and infrastructure partners.
Enjoy building for internal power users and agents, and can make sophisticated ML capabilities feel clear and actionable.
Value in-person collaboration and want to help shape a growing Bellevue-based team.
This role is based in Bellevue, Washington. The team works in person and uses that time to move quickly, solve ambiguous problems together, and stay close to the product teams we support.
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 Washington Jobs in Seattle, WA Seattle city guide Washington state guide King 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 Seattle, WA. Below is what the official statistics say about living and working there.
How Seattle compares. Among the 80 largest places in Washington, Seattle is #1 by population, #76 for homeownership (#1 = highest), #8 for college degrees (#1 = most), #8 for remote work (#1 = most). Its county, King County, is #1 of 39 counties for average pay ($132,279).
Seattle has 754,195 residents (ACS 2020–2024), about 9.6% of the population of Washington. It covers 84 square miles of land, which works out to roughly 8,979 people per square mile. The median age is 35.6, 7% younger than the state median (35.6 against 38.3).
The median gross rent is $2,030 a month (rent plus utilities), 15% above the state median ($2,030 against $1,760). Over a year that is 19.7% 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 $938,600, which is 7.6 times the median household income ($123,860); a ratio above 5 usually means buying is out of reach without savings or a second income. 43.7% of households own their home, 31% below the state average (43.7% against 63.8%). A low ownership share points to a rental-heavy market with more apartments and shorter stays.
The Seattle-Tacoma-Bellevue, WA metropolitan area has 2,086,210 jobs in the BLS wage survey, and the median pay across all occupations is $72,610 a year, 42% above the national median ($72,610 against $50,980). The biggest occupation groups are office and administrative support (212,900 jobs, median $59,660); business and financial operations (201,160 jobs, median $101,950); computer and mathematical (194,970 jobs, median $156,000). The area is most specialised in computer and mathematical (2.8 times) and architecture and engineering (1.4 times), where the share of workers is well above the national share. The best-paying groups with at least 5,000 jobs are management ($168,110) and computer and mathematical ($156,000). In 2026M09 the unemployment rate of King County was 4.8%. 74.0% of residents aged 16 and over are in the labour force. The city lies in King County; its jobs, pay by industry and GDP are on the county page.
Among workers, 36.6% drive alone, 11.9% use public transit, 8.1% walk, 34.8% work from home. 13.9% of workers commute 45 minutes or more, 18% below the state average (13.9% against 16.9%). 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.
68.5% of adults aged 25 and over hold a bachelor's degree or higher, 73% above the state share (68.5% against 39.6%). 20.1% of residents were born outside the United States, 31% above the state share (20.1% against 15.4%). The poverty rate is 9.9%, about the same as the state rate (9.9% against 9.9%).
The warmest month is Aug, averaging 65°F (18.3°C), and the coolest is Dec at 39°F (3.8°C). About 1,230 mm (48 inches) of precipitation falls in a year; Nov is the wettest month (188 mm) and Jul the driest (19 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: Mercer Island (7 miles, rent 23% higher); Bainbridge Island (7 miles, rent 8% higher); Kirkland (9 miles, rent 18% higher); Bellevue (9 miles, rent 27% higher). Rent differences are against Seattle; use the Compare tab to put any two cities side by side.
Full guide to Seattle →Washington guideAll jobs in Seattle
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Places within 50 miles (straight line) of Seattle, WA 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 ⇅ |
|---|---|---|---|---|---|---|---|
| Seattle, WA | 0 mi | $2,030 | $938,600 | $123,860 | 13.9% | n/a | Jobs |
| Mercer Island, WA | 7 mi | $2,502 | $2,000,001 | $219,069 | 8.7% | n/a | — |
| Bainbridge Island, WA | 7 mi | $2,194 | $1,155,900 | $172,188 | 37.2% | n/a | — |
| Kirkland, WA | 9 mi | $2,401 | $1,115,400 | $150,414 | 10.8% | n/a | — |
| Bellevue, WA | 9 mi | $2,572 | $1,340,300 | $165,576 | 11.1% | n/a | Jobs |
| Shoreline, WA | 10 mi | $1,985 | $811,100 | $112,751 | 17.1% | n/a | — |
| Burien, WA | 10 mi | $1,782 | $638,800 | $91,318 | 15.5% | n/a | — |
| Kenmore, WA | 10 mi | $1,949 | $920,800 | $139,764 | 19.3% | n/a | — |
| Tukwila, WA | 10 mi | $1,898 | $489,000 | $78,381 | 14.6% | n/a | — |
| Redmond, WA | 12 mi | $2,409 | $1,167,800 | $162,560 | 9.8% | n/a | Jobs |
| Renton, WA | 12 mi | $1,998 | $672,600 | $100,432 | 22.0% | n/a | Jobs |
| Mountlake Terrace, WA | 12 mi | $2,004 | $667,300 | $107,687 | 17.8% | n/a | — |
| SeaTac, WA | 12 mi | $1,660 | $519,700 | $81,104 | 14.7% | n/a | — |
| Bothell, WA | 13 mi | $2,346 | $925,100 | $140,427 | 16.6% | n/a | — |
| Edmonds, WA | 13 mi | $1,903 | $890,100 | $122,449 | 16.7% | n/a | — |
| Bothell West, WA | 14 mi | $2,511 | $824,900 | $153,449 | 29.0% | n/a | — |
| Lynnwood, WA | 15 mi | $1,742 | $686,900 | $77,704 | 19.6% | n/a | Jobs |
| Sammamish, WA | 15 mi | $2,857 | $1,407,300 | $239,690 | 18.2% | n/a | — |
| Issaquah, WA | 15 mi | $2,590 | $963,000 | $154,669 | 12.8% | n/a | — |
| Fairwood, WA | 15 mi | $2,233 | $733,200 | $122,134 | 28.0% | 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 Seattle, WA 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 ⇅ |
|---|---|---|
| Seattle, WA | 0 mi | 754,195 |
| San Francisco, CA | 684 mi | 830,235 |
| San Jose, CA | 714 mi | 990,138 |
| Los Angeles, CA | 962 mi | 3,857,263 |
| Denver, CO | 1,024 mi | 718,877 |
| San Diego, CA | 1,059 mi | 1,389,526 |
| Phoenix, AZ | 1,108 mi | 1,642,323 |
| Oklahoma City, OK | 1,524 mi | 697,125 |
| Fort Worth, TX | 1,658 mi | 963,194 |
| Dallas, TX | 1,681 mi | 1,307,930 |
| Chicago, IL | 1,732 mi | 2,711,226 |
| Austin, TX | 1,769 mi | 979,539 |
| San Antonio, TX | 1,784 mi | 1,479,835 |
| Indianapolis, IN | 1,869 mi | 885,860 |
| Houston, TX | 1,888 mi | 2,328,253 |
| Columbus, OH | 2,009 mi | 914,802 |
| Charlotte, NC | 2,283 mi | 903,844 |
| Philadelphia, PA | 2,374 mi | 1,579,706 |
| New York, NY | 2,407 mi | 8,483,844 |
| Jacksonville, FL | 2,452 mi | 977,670 |
| City ⇅ | Straight-line distance ⇅ | Open jobs ⇅ |
|---|---|---|
| Bellevue, WA | 9 mi | 263 |
| Redmond, WA | 12 mi | 385 |
| Lynnwood, WA | 15 mi | 5 |
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A private-sector role in technology (data, analytics and ai) listed 46 days ago. The full description is on this page and on the employer's page.
Seattle, WA. A remote or flexible location is listed; confirm with the employer which states are accepted.
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The listing does not publish pay, and we could not match the title to one official occupation.
Median rent in Seattle is $2,030 a month and median household income $123,860 (ACS 2020–2024).
It was posted on 2026-09-24 (46 days ago). Jobs older than 90 days are not shown.
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