CoreWeave Careers Guide: Teams, Hiring & Benefits

You’re here because you want a clear, candid look at CoreWeave careers—what we build, how we work, and how to get hired—with proof points that matter. We’ve been recognized by USA Today’s Top Workplaces program and power AI workloads on cutting-edge GPU clusters, including GB200/Blackwell-ready designs.

This CoreWeave careers blog is your definitive hub:

• life at CoreWeave
• teams and projects
• benefits
• interview process
• remote policy
• day‑in‑the‑life spotlights

Whether you’re an infra engineer, SRE, data center pro, security leader, or product operator, you’ll find what you need and clear next steps to apply.

What is CoreWeave? The 60‑second overview

CoreWeave builds an AI‑native cloud purpose‑built for high‑performance compute with GPUs, fast interconnects, and a developer‑first control plane. We’re known for bare‑metal Kubernetes, Slurm scheduling, and high goodput across large‑scale AI training clusters. Independent analyses and public benchmarks frequently cite our performance and reliability.

We serve AI companies, research labs, and quant firms that need predictable, high‑throughput training and inference at scale. Examples include:

• dense GPU pools with InfiniBand
• liquid cooling for power efficiency
• orchestration via Kueue, Ray, and our Slurm‑on‑Kubernetes (SUNK) patterns

The takeaway: this is a place to build AI infrastructure that measurably moves the needle.

Mission, trajectory, and why we’re hiring now

Our mission is to make mission‑critical AI infrastructure accessible, performant, and reliable for builders everywhere. Growth is driven by expanding data center capacity, customer wins in AI/ML and finance, and sustained demand for GPU‑dense clusters. Recent recognition (e.g., Energage Top Workplaces) underscores momentum and culture.

We’re hiring across engineering, data center operations, networking, product, and security to scale capacity, ship new platform features, and sustain 24/7 reliability.

Near‑term priorities include:

• Blackwell/GB200 enablement
• Slurm and Ray orchestration at fleet scale
• improvements to our Mission Control portal

If you want outsized ownership on real production systems, now is the time.

Is CoreWeave a good place to work? Proof and culture signals

You should be confident the work is meaningful, the culture is healthy, and the bar is clear. We pair deep technical rigor with a people‑first approach, and we share evidence so you can evaluate us on facts, not fluff.

We emphasize impact, mentorship, and pragmatic velocity—ship in days, not quarters. We also protect time for quality and incident learning. Expect blameless postmortems, clearly defined ownership, and a bias for simplicity.

The takeaway: strong outcomes and strong support are not mutually exclusive here.

Awards and recognition (USA Today Top Workplaces, Energage badges)

External validation matters when you’re choosing a team. CoreWeave has been recognized by USA Today’s Top Workplaces program (2024) and Energage Top Workplaces (2024), reflecting employee feedback on culture, leadership, and alignment. These awards accompany customer proof across AI and quant finance.

Third‑party performance write‑ups (e.g., SemiAnalysis ClusterMAX Platinum) and public benchmarking wins (e.g., MLPerf submissions cited in our engineering blog) reinforce technical credibility. Awards aren’t the goal; they’re a signal that our environment supports high performance and growth.

Values in action: how we collaborate, ship, and learn

We optimize for ownership, clarity, and craft. Teams write crisp design docs, demo weekly, and iterate behind feature flags to de‑risk rollouts. Engineers pair on hard incidents and publish postmortems that focus on systems, not blame. “We ship fast because we measure what matters,” as one hiring manager puts it.

Learning is built into the operating rhythm: architecture reviews, reliability game days, and small RFCs that drive change. When a decision is irreversible or high‑impact, we prefer written tradeoffs and explicit SLOs.

The takeaway: you’ll do your best work when process amplifies judgment, not replaces it.

Teams we’re hiring for and what they do

You’ll move faster when you know where your skills fit and the outcomes each team owns. Below is a quick map of job families, responsibilities, and sample projects to help you self‑select.

This section links directly to work you’ll do—tools, on‑call expectations, and impact areas—so you can decide if CoreWeave is right for you versus Big Tech or an early‑stage startup. If you want scope plus speed on systems that matter, read on.

AI/ML Infrastructure Engineering

AI/ML Infra engineers build and optimize the training and inference substrate across GPUs, schedulers, and data services. You’ll work on Slurm on Kubernetes (SUNK), Kueue queueing, Ray clusters, model runtime optimization (e.g., TensorRT), and CAIOS storage throughput improvements.

• Responsibilities: scheduler strategies, cluster scaling, GPU packing, model routing, and performance debugging.
• Sample projects: enable GB200/Blackwell clusters; optimize interconnect topologies; improve goodput on multi‑node training; integrate Ray autoscaling with Kueue.
• Must‑have skills: Kubernetes, Linux performance, GPU tooling, distributed systems basics, and a bias for measurement.

The takeaway: this is hands‑on systems engineering at the frontier of AI compute efficiency.

Platform/SRE and Networking

Platform/SRE keeps our control plane, core services, and customer workloads reliable and observable. Networking engineers design and operate low‑latency fabrics (e.g., InfiniBand, RoCE), EVPN underlays, and data center routing at scale.

• Responsibilities: SLOs/SLA design, incident response, CI/CD, observability (Prometheus/Grafana), eBPF tracing, capacity planning, and change management.
• On‑call: rotating, follow‑the‑sun coverage with well‑defined runbooks, tiered paging, and post‑incident review.
• Tooling: Kubernetes, Terraform, Ansible, SONiC/Cumulus, NetBox, and traffic engineering for GPU clusters.

We measure goodput and time‑to‑mitigation, not just uptime.

The takeaway: you’ll own real reliability levers and see your work reflected in customer outcomes.

Data Center Operations and Hardware

DC Ops delivers the metal: rack/stack, power/cooling, cabling, and hardware lifecycle across GPU‑dense clusters. You’ll bring up new sites, maintain liquid cooling loops, and keep InfiniBand fabrics healthy under load.

• Responsibilities: install/commission servers, diagnose hardware faults, maintain IB switches, perform burn‑in, and execute change windows safely.
• Environment: hands‑on, safety‑first, with shift coverage to support 24/7 operations and scheduled maintenance windows.

If you love tactile engineering with visible impact, this team keeps the fleet fast, cool, and reliable.

Security and Compliance

Security engineers safeguard isolation, determinism, and customer trust across infrastructure and software. Work spans identity, secrets, tenant isolation, vulnerability management, and incident readiness.

• Responsibilities: threat modeling, guardrail automation (OPA/Rego), secret management, hardening pipelines, and tabletop exercises.
• Compliance: operate to industry‑standard frameworks (e.g., SOC 2) with pragmatic controls that don’t slow builders down.

Takeaway: you will partner deeply with SRE and product to embed security into default workflows.

Product, GTM, and Operations

Beyond code and clusters, we need product managers, solutions engineers, marketing, finance, and operations to translate platform capabilities into customer value. You’ll work cross‑functionally to shape roadmaps, tell the story, and remove friction from adoption.

• Responsibilities: roadmap definition, customer discovery, solutions design, pricing/packaging, and operational excellence.
• Sample projects: launch Mission Control features, publish performance guides, build onboarding playbooks for new AI training tiers.

This is a place to turn technical advantage into market impact—fast.

How we work: tech stack, scale, and impact

Candidates evaluating AI cloud careers want to know the stack and scale they’ll own. We build with GPUs, fast networking, and a developer‑first control plane, and we optimize for measured outcomes like goodput and time‑to‑train.

You’ll ship features that land in production across GPU clusters used by demanding customers, including quant researchers and AI labs. Public case studies and third‑party validation (e.g., SemiAnalysis) reflect how we run at scale; our engineering blog shares the details.

Our stack at a glance: GB200/Blackwell GPUs, bare‑metal K8s + Slurm, Ray, CAIOS

Here’s what you’ll touch in day‑to‑day work:

• GPUs: NVIDIA H100/H200 today and GB200/Blackwell‑ready designs.
• Orchestration: bare‑metal Kubernetes, Slurm on Kubernetes (SUNK), and Kueue.
• Distributed compute: Ray/Anyscale, MPI, and Triton/TensorRT‑LLM for inference.
• Storage: CAIOS with high‑throughput datapaths for training/inference.
• Networking: InfiniBand/RoCE, EVPN fabrics, and traffic engineering for GPU pods.
• Control plane: Mission Control—our portal and APIs for users and operators.

Takeaway: if you want to build where schedulers, networks, and runtimes meet, this is your toolbox.

Reliability and security at scale: goodput, isolation, and performance under load

Performance isn’t just peak TFLOPs—it’s sustained goodput under real workloads. We design for high cluster utilization, predictable job latency, and fast recovery, with single‑tenant isolation options for sensitive workloads.

Expect SLOs for scheduling latency and job success rates, policy‑driven QoS, and incident routines that favor automation over heroics. We optimize memory bandwidth, interconnect topology, and kernel parameters to protect training throughput.

The takeaway: operational excellence is a first‑class feature here.

Career growth, learning, and ownership

Great careers are built on scope, mentorship, and real chances to lead. We invest in onboarding, learning, and internal mobility so you can grow without changing companies.

If you’re choosing between Big Tech and a startup, consider this: CoreWeave offers the ownership and speed of a builder culture with the scale and customer stakes of a top hyperscaler. You won’t wait quarters to ship.

Onboarding, mentorship, and internal mobility

You’ll get a 30‑60‑90 plan, a mentor/buddy, and clear outcomes for early wins. We bias toward shipping small changes in week one and expanding scope with support.

Managers run regular growth check‑ins, and internal mobility is encouraged once you’ve hit goals on your current team.

The takeaway: you’ll have a path to mastery and the space to pursue it.

Learning budgets, conferences, and open-source contributions

We support ongoing learning with an annual stipend, conference attendance (e.g., KubeCon, re:Invent, NeurIPS), and time for skill‑building. Engineers contribute to and upstream fixes in projects like Kueue, Slurm, and Ray when it advances the work.

Expect internal tech talks, reading groups, and RFC reviews that make learning a team sport.

The takeaway: curiosity is part of the job description.

Compensation, benefits, and work flexibility

You deserve transparency on the basics so you can make an informed decision. We offer competitive compensation, equity, comprehensive benefits, and flexible work where the role allows.

Policy details evolve as we grow; the Careers site always has the most current information. Below is a summary to set expectations.

Health, retirement, equity, and time off—what to expect

• Medical, dental, and vision coverage for employees and dependents
• Retirement plans with employer support
• Equity grants aligned to role and level
• Generous paid time off, company holidays, and sick time
• Family support: leaves, caregiver resources, and well‑being programs

Benefits vary by region; refer to the job posting for location‑specific details and eligibility.

Remote/hybrid policy, locations, and time zones

• Many engineering, product, and GTM roles are remote‑friendly within approved regions and time zones.
• Data center and some hardware/network roles are onsite due to the nature of the work.
• Hybrid options exist near office or site locations; travel may be required for team events or on‑site work.

Check each posting for location requirements and time‑zone alignment.

Visa sponsorship and relocation support

• Sponsorship and relocation depend on role, seniority, and location.
• We consider visa support for critical roles where local hiring is not feasible.
• Relocation packages may be offered for onsite or leadership positions.

If you need sponsorship, apply and note your situation; our recruiters will advise on options.

Hiring process: what to expect and how to prepare

A transparent hiring process reduces anxiety and helps you perform your best. We aim for speed without surprises, and we share prep tips so you can focus on signal.

Typical timelines run a few weeks end‑to‑end, depending on role and scheduling. We’ll keep you updated at each step and offer feedback where possible.

Application → recruiter screen → technical assessment → panel → offer

• Application: submit resume/links; we evaluate for role fit and impact.
• Recruiter screen (30–45 min): role, team, expectations, and your interests.
• Technical assessment: live or take‑home aligned to the job (e.g., systems design, debugging, lab).
• Panel: 3–5 interviews covering technical depth, collaboration, and values.
• Debrief & offer: references as needed; decisions typically within 1–5 business days.

Timelines vary; complex roles or travel can extend the process.

Sample interview questions and preparation tips

• Infra/Platform: design a GPU training platform; scale Slurm on Kubernetes; debug noisy‑neighbor issues; propose SLOs for batch vs. interactive jobs.
• SRE/Networking: trace packet loss in a multi‑tenant cluster; design EVPN underlay; run an incident from page to postmortem.
• Security: threat model a control plane; enforce isolation with policy; incident tabletop.

Prep tips: review fundamentals, practice whiteboard/system design, read recent engineering blog posts, and bring real examples. Common pitfalls: skipping requirements, ignoring tradeoffs, and not instrumenting solutions.

Day in the life: short employee spotlights

Stories make it easier to picture the work and whether you’ll enjoy it. These snapshots reflect common weeks across teams—tools, rituals, and outcomes.

They’re condensed for readability, but the essence is true: you’ll ship, learn, and collaborate with people who care about doing it right.

Infra engineer (training platform) — a week at scale

Monday kicks off with a design review to add Kueue‑aware preemption to improve Ray cluster turn‑up times. You ship a feature flag to canary a new Slurm partition across a handful of GB200 nodes.

Midweek, a throughput dip on a multi‑node training job triggers investigation; you trace it to an interconnect queue config and roll out a fix via Mission Control. Friday’s demo shows a 7% goodput gain on a representative workload and a plan to roll it fleet‑wide next week.

Data center technician — keeping clusters healthy

You start with a hot/cold aisle walk, then commission a batch of GPU servers with burn‑in and firmware baselines. An InfiniBand link flap surfaces in monitoring; you verify optics, reseat, and document the resolution before the next maintenance window.

The afternoon is liquid cooling maintenance: checking flow rates, replacing a pump, and validating thermal performance under load. You close the week with a site change window to add capacity, following a detailed MOP and peer review.

Security engineer — isolation and incident readiness

On Monday, you run a tabletop exercise simulating a credentials leak and validate playbooks across SRE and product. You deploy a new OPA policy to enforce GPU quota limits per namespace and add detections for anomalous scheduler events.

Midweek, you harden build pipelines, rotate secrets, and update guardrails in Mission Control. Friday’s readout covers mean time to detect, policy coverage, and a backlog cut focused on least‑privilege automation.

Early careers: internships and new grad roles

If you’re early in your career, you’ll get real projects, mentorship, and clear outcomes. Interns and new grads are paired with hosts, ship scoped features, and present their work at the end of the program.

Recruiting typically opens months ahead of summer; apply early and include projects that show how you learn. Roles span engineering, data center operations, and product/systems adjacent functions—check postings for timelines and eligibility.

FAQs about working at CoreWeave

Is CoreWeave remote-friendly?

Yes—many roles are remote within approved regions and time zones. Some positions (data center, certain hardware/network jobs) require onsite work due to physical infrastructure. Hybrid options exist near office or site locations. Each job posting lists location eligibility, time‑zone expectations, and any travel needs.

What’s the typical timeline from application to offer?

Most candidates complete the process in 2–5 weeks, depending on role complexity and scheduling. Stages include a recruiter screen, technical assessment, and a panel interview. We aim for fast, transparent decisions and provide status updates throughout. Travel or specialized assessments can extend timelines.

Do you hire interns or new grads?

Yes. We offer internships and select new‑grad roles across engineering, data center operations, and product‑adjacent teams. Recruiting typically begins months before summer start dates. Apply early, include relevant projects or coursework, and note your preferred timeframe and location in the application.

How do teams handle on-call and incidents?

SRE and platform teams use rotating, follow‑the‑sun on‑call with tiered paging, clear runbooks, and automated remediation where possible. Incidents are blameless with written postmortems and action items. Product and security partner closely for cross‑functional events, with communication and ownership defined upfront.

Explore open roles and next steps

You’ve seen the work, the teams, and the process—now make your move. We keep our Careers site up to date with roles, locations, and requirements so you can apply with confidence.

If timing isn’t right, stay close: join our talent community to hear about new roles, events, and engineering updates first.

Browse open positions by team and location

Visit the Careers page to filter by team (AI/ML Infra, SRE/Networking, Security, Product/GTM, Data Center) and location or remote eligibility. Read role requirements carefully and tailor your resume to relevant outcomes and tools (e.g., K8s/Slurm, Ray, InfiniBand).

Join our talent community for future roles

Not ready to apply? Share your interests and resume to get notified when matching roles open. You’ll receive curated updates on hiring areas, engineering blog posts, and events so you can time your application.

Life at CoreWeave and Careers links

Explore Life at CoreWeave for culture stories, benefits snapshots, and employee spotlights. When you’re ready, head to CoreWeave jobs on the Careers site to submit your application. We’re excited to meet you and help you do the best work of your career.