At a Glance
- Tasks: Design and evolve LLM evaluation frameworks for cutting-edge AI systems.
- Company: Early-stage AI company focused on innovative agentic systems.
- Benefits: 0.5% equity, 30 days holiday, hybrid work, and growth opportunities.
- Other info: Fast-paced culture with potential to become Head of AI as the company grows.
- Why this job: Shape the future of AI while working closely with founders in a dynamic environment.
- Qualifications: 2-5 years in backend/software engineering and hands-on AI experience.
The predicted salary is between 60000 - 80000 € per year.
We’re working with an early-stage AI company building production-grade agentic systems and workflow automation products. They are now hiring an AI Engineer to take ownership of their evaluation infrastructure and help shape the future direction of their AI capability. This is not a pure research role or prompt engineering position. The focus is on production AI systems, eval frameworks, agent orchestration, and engineering reliability.
You will work directly with founders and engineers to evolve their existing V1 eval framework into a scalable, production-ready V2 system integrated into deployment workflows and engineering pipelines. The environment is fast moving, highly technical, and suited to engineers who enjoy ownership, ambiguity, and building systems end to end.
What You’ll Work On
- Designing and evolving LLM evaluation frameworks for production systems
- Building eval infrastructure directly into deployment and engineering pipelines
- Improving agent reliability, reasoning quality, and orchestration logic
- Defining prompting strategies, sub-agent interactions, and reasoning trade-offs
- Making architectural decisions around latency, reasoning depth, performance, and reliability
- Working closely with founders on product and technical direction
- Helping shape the long-term AI engineering function as the company scales
What They’re Looking For
- 2 to 5 years of backend or software engineering experience
- 1 to 2 years of hands-on AI engineering experience in production environments
- Experience deploying LLM applications or agentic systems into production
- Strong engineering fundamentals across APIs, backend systems, infrastructure, and architecture
- Experience designing evals, benchmarking systems, or AI testing workflows
- Ability to translate business requirements into measurable evaluation frameworks
- Comfortable discussing production failures, trade-offs, and engineering decisions
- Strong ownership mentality and ability to operate in fast-moving environments
Nice To Have
- Experience from start-ups or YC-style environments
- Exposure to multi-agent systems or orchestration frameworks
- Experience integrating eval tooling into CI/CD or deployment systems
- Customer-facing or stakeholder-facing exposure
- Side projects or experimentation around evals, benchmarking, or agent systems
Package
- 0.5% equity
- 30 days holiday plus bank holidays
- Hybrid working in Clapham Junction
- Opportunity to grow into a future Head of AI position as the company scales
Interview Process
- Introductory call
- Founder meeting
- Technical architecture and eval discussion
- Scenario-based onsite session
Machine Learning Engineer in Slough employer: DeepRec.ai
Join an innovative early-stage AI company in Clapham Junction, where you'll have the opportunity to take ownership of cutting-edge evaluation infrastructure and shape the future of AI capabilities. With a hybrid working model, 30 days of holiday, and the potential for equity, this role offers a dynamic work culture that fosters growth and collaboration with founders and engineers. Embrace the chance to evolve into a leadership position as the company scales, all while working in a fast-paced environment that values technical excellence and creative problem-solving.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in Slough
✨Tip Number 1
Get your networking game on! Connect with folks in the AI and machine learning space, especially those who are already working at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to LLMs or agent systems. This gives you a chance to demonstrate your hands-on experience and engineering prowess, making you stand out in interviews.
✨Tip Number 3
Prepare for technical discussions! Brush up on your knowledge of eval frameworks and production AI systems. Being able to discuss your thought process and decisions around engineering reliability will impress interviewers and show you're ready for the challenge.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to take ownership and build systems end to end. Your next big opportunity could be just a click away!
We think you need these skills to ace Machine Learning Engineer in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your backend or software engineering experience, especially in AI environments, to show us you’re the right fit for the Machine Learning Engineer role.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re excited about this position and how your background aligns with our needs. Share specific examples of your work with LLM applications or agentic systems to grab our attention!
Showcase Your Projects:If you’ve worked on any side projects or experiments related to evals or benchmarking, don’t hold back! Include these in your application to demonstrate your hands-on experience and passion for AI engineering.
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 don’t miss out on any important updates during the process!
How to prepare for a job interview at DeepRec.ai
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals and the specific technologies mentioned in the job description. Be ready to discuss your past experiences with LLM applications and agentic systems, as well as any relevant projects you've worked on.
✨Show Your Ownership Mentality
This role requires a strong sense of ownership, so be prepared to share examples of how you've taken charge of projects in the past. Discuss how you’ve navigated ambiguity and built systems from the ground up, highlighting your problem-solving skills.
✨Prepare for Technical Discussions
Expect to dive deep into technical architecture and evaluation frameworks during the interview. Familiarise yourself with common architectural decisions around latency and performance, and be ready to discuss trade-offs you've made in previous roles.
✨Engage with Founders
Since you'll be working closely with the founders, show genuine interest in their vision for the company. Prepare thoughtful questions about their goals and how you can contribute to shaping the AI engineering function as they scale.
