Staff Software Engineer, Inference

Staff Software Engineer, Inference

Full-Time 72000 - 88000 £ / year (est.) No working from home possible
United States Digital Space LLC

At a Glance

  • Tasks: Lead the development of a cutting-edge cloud platform for AI and ML workloads.
  • Company: Join CoreWeave, a pioneering tech company transforming the AI landscape.
  • Benefits: Enjoy competitive pay, flexible vacation, and comprehensive health benefits.
  • Other info: Dynamic growth environment with endless opportunities for innovation and collaboration.
  • Why this job: Make a real impact in AI while working with top industry talent.
  • Qualifications: 8+ years in software engineering with expertise in distributed systems and Kubernetes.

The predicted salary is between 72000 - 88000 £ 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. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

We're proud to be a Living Wage accredited Employer.

Location: London, England

What You'll Do:

CoreWeave's Inference team builds and operates the core cloud platform powering massive-scale GPU workloads for AI/ML, VFX, rendering, and real-time inference. Our stack is engineered for speed, scale, and cost efficiency—providing a powerful alternative to traditional hyperscalers where infrastructure is our core product operated at massive scale.

About the role:

As a Staff Software Engineer on the Inference team, you will operate as a technical leader across multiple teams and services, driving architecture, performance, and reliability for CoreWeave's Kubernetes-native inference platform. You will define and lead complex, cross-cutting design initiatives spanning request routing, adaptive scheduling, GPU resource management, and cost-per-token optimisation under strict P99 SLAs. In this high-impact role, you will implement advanced inference optimisations—such as speculative decoding and KV-cache reuse—while establishing performance benchmarking frameworks, guiding cross-functional alignment across infrastructure boundaries, and raising the bar for engineering rigour and observability practices across the organisation.

Who You Are:

  • Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
  • 8+ years of experience building large-scale distributed systems or cloud platforms, with a proven track record of leading cross-team or organisation-level technical initiatives at scale.
  • Strong coding proficiency in Go, Python, or C++.
  • Deep expertise in Kubernetes at production scale, including orchestration, scheduling, and service design.
  • Strong understanding of networked systems, performance optimisation, and distributed system design.
  • Hands-on engineering experience with inference systems, including batching/micro-batching strategies, caching, memory optimisation, mixed precision (BF16/FP8), and streaming token delivery.
  • Demonstrated ability to systematically improve tail latency (P95/P99) and platform reliability through metrics-driven engineering.
  • Proven experience owning system-wide SLIs/SLOs, capacity planning, autoscaling strategies, and mentoring senior and mid-level engineers.

Preferred:

  • Direct open-source or production contributions to modern inference frameworks (e.g., vLLM, Triton, TensorRT-LLM, Ray Serve, or TorchServe).
  • Deep experience with GPU systems engineering and hardware performance optimisation (e.g., CUDA, NCCL, RDMA, NUMA, or GPU interconnects).
  • Direct exposure to large-scale AI/ML infrastructure or hyperscale cloud 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.

You love to: Scale highly complex distributed architectures and mentor engineering cohorts to elevate technical standards across an organisation.

You're curious about: Pioneering low-latency inference optimisations and finding innovative shortcuts to optimise cost-per-token performance.

You're an expert in: Metrics-driven engineering, troubleshooting micro-bottlenecks, and delivering stable cloud platforms under strict multi-tenant constraints.

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 take-off, 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!

At CoreWeave, base pay is only one part of our total compensation package. Total compensation includes base salary, equity, flexible vacation policy, and comprehensive benefits. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation.

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.

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.

Staff Software Engineer, Inference employer: United States Digital Space LLC

United States Digital Space LLC is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. With a strong focus on employee well-being and flexible work options, we provide ample opportunities for professional growth and development, making it an ideal environment for those looking to make a meaningful impact in the field of AI-enabled SaaS engineering.

United States Digital Space LLC

Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Software Engineer, Inference

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We think you need these skills to ace Staff Software Engineer, Inference

Technical Leadership
Kubernetes
Distributed Systems
Cloud Platforms
Go
Python
C++

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 United States Digital Space LLC.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC 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 United States Digital Space LLC

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 United States Digital Space LLC 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.