Staff Applied Research Engineer

CoreWeave; Bellevue (WA); On-site; USD 207,000 - 275,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with generous match

Equity awards

Tuition reimbursement

Flexible PTO

Catered lunch daily

Job summary

CoreWeave's OpenPipe team is seeking an applied research engineer to advance continuous learning for self-improving agents. You will generate research ideas, validate directions across real customer tasks, and harness a GPU-rich stack to push production-ready solutions.

You should have 8+ years in ML or a PhD with 4+ years, with deep expertise in LLM training methods, supervision, RL, and policy optimization, and proven ability to lead cross-functional initiatives and mentor peers.

Qualifications

• 8+ years of experience in machine learning or applied research, or a PhD with 4+ years of relevant industry experience.
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Responsibilities

• Generate and investigate research ideas towards solving remaining obstacles to continuous learning in production.
• Validate research directions across real customer tasks with the broader OpenPipe team.
• Leverage GPU compute to drive experiments and production deployments.
• Collaborate across engineering to ship robust AI capabilities.

Skills

ML / Applied research

LLM training methods

Reinforcement learning

Production deployment

Cross-functional leadership

Mentoring engineers

Education

PhD with 4+ years experience

Tools

Megatron

Kubernetes

Temporal

Postgres

FastAPI

Job description

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

What You’ll Do

The OpenPipe team at CoreWeave is building tools to help agents learn from experience. This is a critical step to make agents reliable enough to perform long tasks autonomously, in the same way human employees are. We’re systematically identifying and solving the major bottlenecks between today’s tech and those future self‑improving agents, and we’ve already released:

• Released ART, the easiest library for getting started with RL.
• Developed RULER, a general‑purpose reward function that works across many diverse tasks.
• Built Serverless RL, an elegant API that gives RL practitioners full control over their data, environment and reward function while letting them outsource the headaches of managing GPU infrastructure.

These releases have a theme: we are systematically tackling each major roadblock to successfully training self‑improving agents. Several serious challenges remain—building simulated environments often requires substantial human labor, and existing training methods are not data efficient enough. We’re laser‑focused on solving these problems and making self‑improvement a reality for agent developers.

In startup terms, this is a classic hard‑tech bet. Our roadmap involves substantial technical risk; there are still major technical problems we’re facing without a proven solution. However, there is very little market risk. We’ve worked closely with the teams building agents at many of the top AI‑native startups as well as large enterprises. If we can build this, everyone will want it. A self‑improving agent that learns from experience the way a human employee would could quickly capture a large fraction of the total inference market, which is worth tens of billions of dollars today and will be worth hundreds of billions in a few years.

About The Role

You have trained LLMs to be SOTA on specific tasks. You have opinions on whether sequence‑level or token‑level importance ratios are more effective. You probably shared the ScaleRL paper in your group chats, and kicked off a few ablations after you read it.

This is an applied research role. You will be expected to generate and investigate research ideas towards solving the remaining obstacles to continuous learning in production. You will work with the broader OpenPipe team to validate these research directions across real customer tasks. We are very GPU rich and are ready to direct an enormous amount of compute at this effort.

Beyond your role’s specific qualifications, we’re looking for strong engineers with great taste. The most important qualification by far is that you learn fast and can ship. This role will inevitably involve a lot of learning on the job; we’re building this airplane as we fly it. Engineers on our team touch everything from CUDA kernels to high‑performance LLM tracing dashboards, and you will have an opportunity to touch many parts of this stack. Although we operate as part of a larger company, the OpenPipe team is small, has a large degree of autonomy, and drives our own roadmap and priorities.

Who You Are

• 8+ years of experience in machine learning or applied research, or a PhD with 4+ years of relevant industry experience.
• Demonstrated success developing LLM training methods or systems that produce meaningful improvements on real‑world tasks.
• Deep expertise in LLM post‑training, including supervised fine‑tuning, reinforcement learning, on‑policy distillation, reward modeling, and policy optimization.
• Strong research judgment, including the ability to identify high‑impact problems, design rigorous experiments, and make decisions from ambiguous results.
• Experience taking research ideas from initial hypothesis through implementation, evaluation, and production deployment.
• Proven ability to set technical direction, lead complex cross‑functional initiatives, and mentor other engineers.

Preferred Qualifications

• Publications, open source contributions, or other demonstrated research impact in reinforcement learning, LLM post‑training, or agent learning.
• Deep experience with distributed training, GPU optimization, and large‑scale model training systems.

Our Stack

We strive to use the best tools for the job when building and deploying our production services. Often that means writing our own custom code, but we also lean on existing frameworks. As part of building Serverless RL, we depend on the following libraries and frameworks (among many others):

• Kubernetes
• Megatron
• Temporal
• Postgres
• FastAPI

Wondering if You’re a Good Fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams—even if you’re not a 100% skill or experience match.

Why CoreWeave?

We work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

What We Offer

We include a competitive salary, equity awards, and a comprehensive benefits program. The base salary range for this role is $207,000 to $275,000. The starting salary will be determined based on job‑related knowledge, skills, experience, and market location.

• Medical, dental, and vision insurance – 100% paid by CoreWeave
• Company‑paid Life Insurance
• Voluntary supplemental life insurance
• Short and long‑term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family‑Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full‑service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

California Applicants

California Consumer Privacy Act.

Equal Opportunity & Accommodations

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: [e-mail].

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicants must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158; (B) eligible to access the export controlled information without a required export authorization; or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

• 1157, or (iv) asylee under 8 U.S.C. § 1158.
• 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency.