At a Glance
- Tasks: Transform AI models into real-world products and optimise systems for performance.
- Company: Join a pioneering company creating an AI-native smart assistant.
- Benefits: Enjoy competitive salary, hybrid/remote work, and opportunities for professional growth.
- Other info: Fast-paced environment with excellent collaboration and career advancement opportunities.
- Why this job: Make a real impact by delivering innovative AI solutions that enhance everyday tasks.
- Qualifications: Strong knowledge of machine learning and experience in deploying models required.
Applied AI Engineer
Location: London, UK (Hybrid) or Remote
Employment Type: Full-Time
Department: Engineering
About the Company
The company is building an AI-native smart assistant designed to help everyday users manage conversations, tasks, organisation, and workflows with minimal prompting. The focus is on creating highly reliable AI systems capable of long-running workflows, persistent context, multi-step reasoning, and real-world task completion. The aim is to significantly reduce the time users spend completing daily tasks through intelligent automation.
The Role
As an Applied AI Engineer, you will be responsible for transforming AI model capabilities into real-world product functionality. You'll own problems end-to-end, working across machine learning, systems engineering, and product development to ensure AI solutions operate reliably in production environments. This role focuses on delivering AI products that work effectively for users at scale—not just in demonstrations.
Key Responsibilities
- Build and deploy AI-powered features from model development through to user experience.
- Design and improve prompts, tools, memory systems, and agent workflows.
- Convert raw model outputs into structured, reliable behaviours.
- Debug and resolve issues across the full stack, including models, orchestration, infrastructure, and user experience.
- Optimise AI systems for latency, reliability, and cost efficiency.
- Develop evaluation frameworks to measure real-world performance.
- Collaborate closely with Product and Engineering teams to solve complex problems and deliver working solutions.
Technology Stack
- Python
- PyTorch
- JAX
- Large Language Models (OpenAI APIs, Llama, Qwen, etc.)
- Inference and Serving Frameworks (e.g. vLLM)
- Vector Databases
Required Experience
Technical Skills
- Strong knowledge of machine learning fundamentals and modern neural network architectures.
- Experience training, fine‑tuning, or deploying machine learning models.
- Ability to write clean, maintainable, production-quality code.
- Experience working across multiple layers of technology, from ML models to infrastructure and product delivery.
Personal Attributes
- Strong problem-solving skills.
- Comfortable working in fast‑paced and ambiguous environments.
- Ability to operate independently and take ownership.
- Continuous improvement mindset with a focus on rapid iteration and delivery.
Success Measures
- Deliver machine learning systems that meet accuracy, latency, and reliability targets.
- Quickly identify and resolve production issues.
- Build maintainable and reproducible training, inference, and data pipeline systems.
- Collaborate effectively across Engineering, Product, and Research teams.
- Drive measurable product improvements using real-world feedback and performance data.
Working Environment
- Work independently with minimal oversight.
- Make sound decisions and exercise strong judgement.
- Move quickly whilst maintaining high quality standards.
- Balance execution with learning and experimentation.
Interview Process
- Up to 3 interview stages.
- Applications reviewed by the technical team.
- Interviews conducted virtually and/or onsite.
- Fast and transparent decision-making process.
- Successful candidates will receive an offer to join the team and contribute to building next-generation AI products.
Applied AI Engineer employer: Futureheads
As a Senior Scala Developer with us, you'll be part of a dynamic team dedicated to delivering impactful solutions for the public sector. We pride ourselves on fostering a collaborative work culture that values technical leadership and innovative problem-solving, offering you the chance to grow your skills while working on meaningful projects. With flexible remote working options and opportunities for long-term engagement, we ensure that our employees are supported in their professional development and well-being.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI 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 Futureheads 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 Futureheads.
✨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 Futureheads.
✨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 Futureheads 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 Applied AI Engineer
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 Futureheads.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Futureheads 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 Futureheads
✨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 Futureheads 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.
