At a Glance
- Tasks: Design innovative intelligent systems that outperform traditional models and tackle complex customer problems.
- Company: Join Callosum, a pioneering company in heterogeneous intelligence and cutting-edge AI solutions.
- Benefits: Enjoy a competitive salary, equity options, private healthcare, and relocation support.
- Other info: Collaborative environment in London with a commitment to inclusivity and equal opportunities.
- Why this job: Be part of a team solving the impossible and shaping the future of intelligent systems.
- Qualifications: Hands-on experience with LLMs and strong production engineering skills required.
The predicted salary is between 70000 - 90000 £ per year.
About Us
Artificial intelligence scaled on a bet - that bigger models, more identical chips, and more data would keep delivering. As problems grow more complex and the requirements of intelligence more diverse, that bet is breaking down. The next era belongs to heterogeneous intelligence: diverse models on diverse chips, each with distinct strengths, co-evolving into systems of capability unreachable by any single model or accelerator. Callosum is the Intelligent Systems company. We built the infrastructure to make that possible. Our co-evolution engine optimises simultaneously across workflows, agents, and silicon. We launched in early 2026 showing orders of magnitude improvements in performance and a shift in the cost-performance frontier that no single chip or model provider can provide. We believe intelligence comes from the system, not the model. We are scientists and engineers solving what others consider impossible. If you thrive on hard problems, and are passionate and energised by the scale of the challenge, we'd love to hear from you.
About the Role
Intelligence comes from the system, not from any single model. Designing those architectures is the core of Callosum's work - and the core of this role. You will design new intelligent systems: configurations of models, decomposition strategies, and coordination patterns that outperform frontier monolithic equivalents on the workloads our customers actually run. The work spans the full arc - from translating an ambiguous customer problem into a precise architectural hypothesis, to prototyping and benchmarking against frontier baselines, to handing a validated design to the team that ships it into production. You will work closely with our forward-deployed engineers, who surface the hardest customer problems, and with engineers on the silicon side of co-design, who expose new hardware properties you can exploit. The systems you build enter our catalogue and get served at scale. This role sits on the software side of co-design. There is a hardware counterpart focused on silicon-level work; the two collaborate continuously.
Who we are looking for
- Substantial hands‑on experience with modern LLMs - not at the API‑consumer level, but at the level of someone who has trained, fine‑tuned, served, or built non‑trivial systems on top of them and understands what is happening underneath.
- Strong production engineering: you ship code, not notebooks.
- Empirical rigour: you benchmark honestly, profile before optimising, and do not claim wins you have not measured.
- The ability to operate without supervision on problems whose shape is not yet clear.
What Stands Out
- Direct experience with multi‑agent or compound systems, LLM inference and serving, reinforcement learning, distillation and fine‑tuning, programmatic prompt or topology optimisation, or structured and constrained generation.
- Open‑source work, research publications, or production deployments at meaningful scale.
- A history of sitting close to users or domain experts and translating their problems into systems that solve them.
What We Offer
- Competitive Salary, determined by skills and experience
- Equity & Ownership
- Private healthcare
- We offer Visa sponsorship and relocation benefits to hire the best in the world
- We work in person at our London office. You'll have the tools, space and setup to do your best work, and if you have specific needs, just tell us
- We're committed to building an inclusive workplace where everyone feels welcome, and believe in equal opportunities for all.
Intelligent Systems Engineer employer: Callosum
Contact Detail:
Callosum Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Intelligent Systems Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Callosum. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to intelligent systems. This gives us a tangible way to see what you can do beyond just words on a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of LLMs and system design. We love candidates who can think critically about complex problems, so practice articulating your thought process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in being part of the Callosum team.
We think you need these skills to ace Intelligent Systems Engineer
Some tips for your application 🫡
Show Your Passion for Intelligent Systems: When writing your application, let your enthusiasm for intelligent systems shine through. Share specific examples of projects or experiences that demonstrate your hands-on expertise with modern LLMs and how you've tackled complex problems in the past.
Be Clear and Concise: We appreciate clarity! Make sure your application is well-structured and to the point. Avoid jargon unless it's necessary, and focus on communicating your skills and experiences in a way that's easy to understand.
Highlight Your Collaborative Spirit: Since we work closely with engineers from different backgrounds, emphasise your ability to collaborate effectively. Mention any experiences where you’ve worked with cross-functional teams to solve challenging problems, as this is key to our co-evolution engine.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re proactive and keen to join our team!
How to prepare for a job interview at Callosum
✨Know Your Stuff
Make sure you have a solid understanding of modern LLMs and their underlying mechanics. Be prepared to discuss your hands-on experience with training, fine-tuning, and deploying these models. Brush up on the latest trends in heterogeneous intelligence and be ready to explain how they relate to the role.
✨Showcase Your Problem-Solving Skills
During the interview, highlight specific examples where you've tackled ambiguous problems. Discuss how you translated customer needs into architectural solutions and the impact of your work. This will demonstrate your ability to operate independently and think critically.
✨Emphasise Collaboration
Since this role involves working closely with both software and hardware teams, be sure to share experiences where you've collaborated across disciplines. Talk about how you’ve communicated complex ideas to non-technical stakeholders or worked with engineers to optimise systems.
✨Be Honest About Your Metrics
When discussing your past projects, focus on empirical rigour. Share how you benchmarked your systems and the honest results you achieved. Avoid exaggerating your wins; instead, emphasise your commitment to measuring performance accurately and learning from the data.