Capacity Deployment Lead - Data Center Operations

3 нед. назад

320k–405k USD / годСШАLeadRemote

capacity planningdata center operationsinfrastructure integrationdeployment managementquality assurancenetwork turn-uphardware vendor coordination

Lead capacity deployment and scaling operations for data center compute infrastructure.

О компании

’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Обязанности

As a Capacity Deployment Lead within 's Data Center Operations (DCO) organization, you will support and scale how we bring new compute capacity online across a growing fleet of partner-operated data centers. Deployment runs from construction kickoff to ready for service (RFS). You are engaged during planning and construction, and on-site and hands-on from EFA through infrastructure delivery and receiving, integration QA, power-on and network turn-up, burn-in and validation, and acceptance. You work with hardware vendors and operations partners for completion of each CU (capacity unit) with a structured handover into production operations and the maintenance program. The scope is compute: accelerator systems, racks, and the infrastructure around them - at the sites in service today and the ones coming online behind them.
This is a program and execution role. You will work with the Global Capacity Delivery Program Lead and the broader Data Center Operations organization, to extend its coverage across more sites and platforms as the fleet grows. Expect 50%+ travel: you get eyes on via boots-on-the-ground for each site in preparation for and during delivery, deployment, QA, and close-out, and your authority comes from being there. Working with vendors and partners, you set direction, priorities, and standards for execution, and you prove results with -owned data rather than self-reported status. What you learn at one site - what worked, what slipped, what should become standard - becomes the playbook for the next wave. If you have delivered data center hardware at scale, are passionate about HPC data centers, & enjoy working in complex, fast-paced environments, we welcome you to apply.
Own deployment outcomes for your assigned sites and data-hall waves: CUs and hall ready-for-service dates met, with exceptions closed out, or risk called early enough for leadership to act.
Engage from construction kickoff and confirm deployment readiness ahead of each wave - floor access, power, network, receiving paths, and partner staffing - working the gaps with the site operations partner and facilities counterparts before racks arrive.
Be on site at key points before and during delivery, deployment, QA, and close-out; verify the work with your own eyes rather than from a dashboard, and support the on-site teams with your direct expertise.
Work with partner's site leadership to ensure success through rack delivery and receiving, integration QA, power-on and network turn-up, and burn-in and validation, setting daily priorities and quality gates and confirming results against -owned ticket and telemetry data.
Validate the handover gate for each CU and data hall: acceptance criteria met, burn-in complete, documentation delivered, spares positioned, ticketing live, and a structured handover into production operations and the maintenance program.
Turn best practices, optimization, and lessons learned from each deployment into program-wide improvements: procedures, checklists, acceptance standards, and metrics, so the next wave runs faster and cleaner than the last.
Extend the deployment program to new sites and platforms, adapting standards and acceptance criteria as the hardware changes.
Communicate deployment status, dependencies, constraints, and risk to engineering, capacity planning, the team that owns the overall site schedule, and leadership.

Будет плюсом

Experience with GPU/accelerator or high-density liquid-cooled infrastructure, including bring-up of liquid-cooled racks.
Experience standing up operations at a new site or data hall, from commissioning handoff through first deployment.
Experience deploying more than one accelerator platform, or introducing a new hardware platform into an existing deployment program.
Experience delivering deployment outcomes inside partner-operated or colocation sites where on-the-floor operations are staffed via third parties.
Familiarity with dense accelerator network cabling, optics, and high-speed interconnect at rack and pod scale.

Условия

The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000 — $405,000 USD

Другое

Have 8+ years of experience in data center operations or hardware deployment as a manager, technical lead or related role, including accountability for delivery milestones.
Can demonstrate a proven track record leading compute or network hardware deployments at a large scale across multiple sites or data-hall waves, from early floor access through ready for service.
Have managed vendors, OEMs, or contract workforces to measurable outcomes: milestones, quality gates, operational reviews, and corrective action.
Possess hands-on technical depth in server, network, and rack-level hardware, enough to independently verify deployment quality and audit vendor claims.
Have built or substantially improved operational processes.
Are comfortable working with schedule, ticket, and telemetry data to drive decisions.
Can travel heavily and work on site for extended stretches, including during delivery surges and turn-up windows. 50% Travel expected.
Possess a bachelor's degree in relevant domain or equivalent practical experience.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that recruiters only contact you from @.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of . Be cautious of emails from other domains. Legitimate recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit .com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to , including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.