At a Glance
- Tasks: Build and operate the inference stack for multimodal agent models in production.
- Company: VC-backed lab creating state-of-the-art computer-use agents.
- Benefits: Competitive salary, innovative projects, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on research and production integration.
- Why this job: Join a cutting-edge team translating research into live products that make an impact.
- Qualifications: Strong software engineering skills, proficient in Python and systems languages.
The predicted salary is between 59400 - 72600 £ per year.
Serving a multimodal agent model in production is a different problem to serving a standard LLM. Context length, tool calls, and computer-use workloads create constraints that require co-designing the inference stack with the model team - not just bolting on a serving framework after the fact. This is a VC-backed challenger lab building state-of-the-art computer-use agents. The inference team owns the full stack from engine layer (vLLM, SGLang) through to serving architecture (disaggregated inference, intelligent routing). The team operates at the intersection of research and production - translating cutting-edge techniques directly into the systems behind live agent products.
What you'll do
- Build and operate the inference stack serving multimodal agentic models in production
- Improve latency, throughput, and cost across the serving stack
- Research and implement inference techniques tailored to agent workloads
- Co-design with the models team on training-time decisions that affect inference behaviour
- Evaluate inference frameworks and hardware platforms and feed findings back into roadmap decisions
- Stay current with advances in inference, model serving, and accelerator technology
What you'll need
- Strong software engineering fundamentals and a solid production track record
- Proficient in Python and at least one systems language - Rust, C++, or Go
- Hands-on experience with PyTorch or JAX in an industry setting
- Experience with inference frameworks: vLLM, SGLang, TensorRT-LLM
- Solid distributed systems fundamentals and experience operating production ML infrastructure
- Working knowledge of modern ML including transformers and multimodal architectures
Optional Bonus
- Research engagement: advanced degree with research output, top-tier publications (NeurIPS, ICML, MLSys, OSDI), or open-source contributions
- GPU kernel work - CUDA, Triton, or similar
- Experience with quantisation, speculative decoding, disaggregated inference, or KV-cache compression
Shortlisted candidates will be contacted within 48 hours.
Research Engineer (Inference & Serving) employer: Axiōma Search
Axiōma Search is an exceptional employer for those passionate about machine learning and time-series forecasting. With a collaborative work culture that prioritises innovation and employee growth, team members are encouraged to explore new ideas and technologies while benefiting from a global network of experts. Located in Europe, the company offers unique opportunities for professional development and the chance to make a significant impact in the field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer (Inference & Serving)
✨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 Axiōma Search 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 Axiōma Search.
✨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 Axiōma Search.
✨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 Axiōma Search 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 Research Engineer (Inference & Serving)
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 Axiōma Search.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Axiōma Search 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 Axiōma Search
✨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 Axiōma Search 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.
