At a Glance
- Tasks: Build and optimise AI runtime layers for edge devices using C++.
- Company: Join a forward-thinking tech group focused on privacy-centric AI solutions.
- Benefits: Fully remote work, competitive pay, and a chance to enhance your skills.
- Other info: Exciting opportunity for growth in a dynamic, innovative environment.
- Why this job: Make a real impact in the AI field while working with cutting-edge technologies.
- Qualifications: Strong C++ skills and experience with AI inference engines required.
The predicted salary is between 50000 - 70000 £ per year.
6 Month Contract Outside IR35 UK Fully Remote
About the Role
Fruition Group are seeking a skilled C++ engineer for our client to help build and optimize the runtime layer powering local AI on edge devices. This role focuses on porting, enhancing, and optimizing inference engines such as llama.cpp, ggml, and ONNX-based runtimes to deliver fast, efficient, and reliable on-device AI performance across diverse hardware environments. You will work close to the metal, improving model loading, memory efficiency, and inference speed while ensuring runtime stability and production readiness. This is an opportunity to contribute to privacy-focused AI systems that operate independently of cloud infrastructure.
Responsibilities
- Deploy and optimize machine learning models for edge and on-device environments using frameworks including llama.cpp, ggml, and ONNX
- Improve inference runtime performance across different CPU and GPU architectures
- Collaborate closely with AI researchers to transition models from research into production-ready deployments
- Support model integration, optimization, and runtime stability throughout the deployment lifecycle
- Integrate advanced AI capabilities into existing products and systems
- Contribute to the ongoing enhancement of local inference infrastructure and tooling
Requirements
- Strong programming skills in C++ with experience building high-performance systems
- Hands-on experience with inference engines such as llama.cpp and ggml
- Understanding of deploying models to specific GPU architectures and optimizing inference workloads
- Solid knowledge of deep learning concepts, transformer architectures, and large language models (LLMs)
- Experience working with ONNX and related model deployment frameworks
- Ability to quickly learn and adapt to new technologies and techniques
- Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent practical experience
- Proven background in AI research and development or production ML systems
Nice to Have
- Experience with JavaScript or cross-platform application integration
- Familiarity with low-level performance optimization and hardware acceleration
- Experience working on edge AI, embedded systems, or privacy-focused AI products
AI Engineer (C++) employer: Fruition Group
Fruition Group is an exceptional employer for AI Engineers, offering a fully remote work environment that promotes flexibility and work-life balance. With a strong focus on cutting-edge technology and privacy-focused AI systems, employees have the opportunity to engage in meaningful projects that enhance their skills and contribute to innovative solutions. The collaborative culture encourages continuous learning and professional growth, making it an ideal place for those looking to advance their careers in AI development.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer (C++)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and C++ communities on LinkedIn or Twitter. Join relevant groups and forums where you can share your knowledge and learn from others. You never know who might have a lead on that perfect job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving C++ and AI. Whether it's GitHub repos or personal projects, having tangible evidence of your expertise can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to C++ and AI. Practice coding challenges and be ready to discuss your past experiences with inference engines like llama.cpp and ggml. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves. Let’s get you that dream job!
We think you need these skills to ace AI Engineer (C++)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your C++ skills and experience with inference engines like llama.cpp and ggml. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your skills can contribute to our mission of building privacy-focused AI systems. Keep it engaging and personal!
Showcase Your Projects:If you've worked on any relevant projects, especially those involving edge AI or model optimization, make sure to mention them. We love seeing practical examples of your work that demonstrate your expertise and creativity.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Fruition Group
✨Know Your C++ Inside Out
Make sure you brush up on your C++ skills before the interview. Be prepared to discuss your experience with high-performance systems and any specific projects you've worked on that involved C++. They might ask you to solve coding problems or explain your thought process, so practice coding challenges related to C++.
✨Familiarise Yourself with Inference Engines
Since the role involves working with inference engines like llama.cpp and ggml, it’s crucial to understand how these frameworks operate. Review their documentation, and if possible, try to implement a small project using them. This will not only help you answer technical questions but also show your enthusiasm for the role.
✨Understand Edge AI Concepts
Get a good grasp of edge AI and how it differs from traditional cloud-based AI. Be ready to discuss the challenges and benefits of deploying models on edge devices. This knowledge will demonstrate your understanding of the role's focus on privacy and efficiency.
✨Prepare for Collaboration Questions
Collaboration is key in this role, so expect questions about teamwork and communication. Think of examples where you've worked closely with researchers or engineers to transition models into production. Highlight your ability to adapt and learn quickly, as this is essential for integrating advanced AI capabilities.
