MLOps Engineer

MLOps Engineer

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Join our team to build and scale AI workflows with cutting-edge technology.
  • Company: CoreWeave, a pioneering cloud platform for AI, is rapidly growing.
  • Benefits: Enjoy competitive salary, health insurance, and a supportive work culture.
  • Other info: Dynamic environment with endless growth opportunities and a focus on innovation.
  • Why this job: Make a real impact in the AI industry while working with top talent.
  • Qualifications: 5-6+ years in MLOps or related fields; strong Python skills required.

The predicted salary is between 63000 - 77000 £ per year.

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.

What You'll Do: CoreWeave’s Physical AI Platform Engineering team builds and scales the data and workflow backbone powering advanced engineering simulation and AI workflows. Our ambition is to become the super‑intelligent AI test lab for the engineering industry, delivering the performant, reliable, and trustworthy data foundation trusted by the world’s largest engineering companies.

About the role: As an MLOps Engineer on the Physical AI team, you will serve as the hands‑on owner for our machine learning operations surface across the end‑to‑end model lifecycle—from experimentation and training through to packaging, deployment, serving, and retirement. You will define and roll out MLOps practices, establish operational SLOs/SLAs, and build automated CI/CD and continuous training pipelines to accelerate the path from experiment to supported production deployment. In this role, you will implement comprehensive model observability, data versioning, and drift monitoring while ensuring robust security and governance controls. Additionally, you will partner closely with product, data science, and core infrastructure teams to optimize GPU compute utilization, resolve cross‑boundary platform incidents, and mentor engineers on production‑grade ML practices.

Who You Are:

  • 5–6+ years of professional experience in MLOps, ML platform engineering, ML infrastructure, or SRE/DevOps for production machine learning systems.
  • Proven experience building, operating, and automating production ML pipelines covering experiment tracking, model registries, artifact versioning, dataset management, and deployment workflows.
  • Deep hands‑on experience implementing observability for ML systems, including monitoring inference availability, latency, throughput, GPU/resource utilization, and data or model drift.
  • Strong background in reliability engineering, including defining operational SLOs, writing runbooks, building automated remediation, and managing incident response for ML workloads.
  • Proficient in Python for platform tooling, infrastructure integration, and pipeline automation, alongside strong infrastructure‑as‑code and CI/CD practices.
  • Comfortable operating containerised, cloud‑native environments using Kubernetes and public cloud platforms.
  • Excellent technical communication and cross‑functional collaboration skills, with a track record of bridging data science and platform engineering teams.

Preferred:

  • Experience as an early or founding MLOps engineer establishing ML platform architecture, standards, and operating models from the ground up.
  • Hands‑on experience operating ML workloads on Kubernetes with GPU infrastructure, distributed training, or large‑scale inference engines.
  • Experience with ML platforms handling test, simulation, or time‑series data (e.g., physical test benches, battery labs, automotive/aerospace R&D) within multi‑tenant SaaS environments.

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 aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk.

  • You love to make the path from ML experiment to production reliable, reproducible, and effortless to operate.
  • You're curious about mapping complex system interactions between data, models, and GPU infrastructure to design for rapid recovery.
  • You're an expert in establishing MLOps best practices, automating model delivery pipelines, and mentoring data scientists on production readiness.

Why CoreWeave? At 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

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organisation's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The starting salary will be determined by job‑related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

To fulfill our obligation to protect client data, successful applicants offered employment with CoreWeave will be required to complete a basic criminal record check, conducted in compliance with GDPR. Employment offers are conditional upon receiving satisfactory check results.

What We Offer: In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

  • Family-level Medical Insurance
  • Family-level Dental Insurance
  • Generous Pension Contribution
  • Life Assurance at 4x Salary
  • Critical Illness Cover
  • Employee Assistance Programme
  • Tuition Reimbursement
  • Work culture focused on innovative disruption

Benefits may vary by location.

Equal Opportunity: 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.

Export Control Compliance: This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant 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.

MLOps Engineer employer: CoreWeave Europe

CoreWeave is an exceptional employer that champions innovation and collaboration, making it an ideal place for a Data Centre Construction Project Manager. With a strong focus on employee growth, competitive benefits including family-level medical insurance and generous pension contributions, and a vibrant work culture that embraces curiosity and entrepreneurial thinking, CoreWeave offers a unique opportunity to thrive in the fast-paced AI cloud sector. Located in London, you will be part of a dynamic team dedicated to delivering best-in-class client experiences while enjoying the perks of working in a Living Wage accredited environment.

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Contact Details:

CoreWeave Europe Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land MLOps Engineer

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at CoreWeave Europe or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to CoreWeave Europe.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like CoreWeave Europe.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like CoreWeave Europe that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace MLOps Engineer

MLOps
Machine Learning Operations
CI/CD Automation
Model Lifecycle Management
Observability for ML Systems
Python
Infrastructure as Code

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at CoreWeave Europe.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at CoreWeave Europe and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at CoreWeave Europe

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If CoreWeave Europe uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.