At a Glance
- Tasks: Design and deploy advanced AI solutions while collaborating with cross-functional teams.
- Company: Leading manufacturer of computer electronics with a focus on innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Exciting projects in a fast-paced environment with excellent career advancement opportunities.
- Why this job: Join a dynamic team to shape the future of AI technology and make a real impact.
- Qualifications: Degree in relevant fields and 2 years of hands-on experience in machine learning.
The predicted salary is between 50000 - 70000 ÂŁ per year.
PC Partner is a leading manufacturer of computer electronics. Our key products are video graphics cards, motherboards and mini-PCs. We are also offering one‑stop electronic manufacturing services to reputable brands all over the world. As one of the leaders in the industry, we leverage our extraordinary research and development capabilities and state‑of‑the‑art production facilities to constantly bring new product ideas and leading‑edge innovations to the market. We endeavour to stay ahead of the industry to ensure success and competitiveness in serving the needs of our customers.
We are building a team of AI Engineers to drive the design and deployment of advanced AI solutions. The role involves selecting and implementing optimal AI models, as well as building data engineering pipelines to support machine learning model training, evaluation and deployment. You will collaborate closely with cross‑functional teams to innovate, execute and deliver AI technologies, ensuring project success through strong technical expertise, effective teamwork and clear communication.
Key Responsibilities- Collaborate with cross‑functional teams to define technical specifications for AI‑driven software solutions.
- Build and maintain robust, scalable data pipelines to support machine learning and AI model training.
- Design and manage data architectures that enable efficient and reliable AI workflows.
- Prepare, clean, and integrate large datasets; design and implement vector databases to support training and inference of machine learning models.
- Design and develop AI models and APIs, integrating them seamlessly into both application software and embedded hardware systems.
- Review codes developed by team members, driving continuous improvement of AI models through algorithm refinement, code optimisation and stakeholder feedback.
- Develop comprehensive test cases; conduct rigorous testing, debugging and bug fixing to ensure high quality, performance and system reliability.
- Train, evaluate and fine‑tune machine learning models to achieve optimal efficiency and low latency.
- Implement MLOps best practices to manage the end‑to‑end software and machine learning lifecycle, including version control, CI/CD pipelines and documentation.
- Collaborate with project leaders to plan, execute, monitor and deliver multiple projects using Agile methodologies.
- Work closely with project teams to deploy machine learning models into production environments and support post‑deployment operations.
- Analyse data to extract meaningful insights and present results to stakeholders to support product and business decisions.
- Conduct research and collaborate with external stakeholders to stay up‑to‑date with the latest AI technologies and industry standards, continuously enhancing development and evaluation processes.
- Min. Degree in Computer Science, Computer Engineering, Data Science, Artificial Intelligence or related fields.
- Min. 2 years of relevant experience in a similar role, with hands‑on experience in designing, developing and deploying machine learning in real‑world applications.
- Proficient in machine learning frameworks and libraries such as TensorFlow and PyTorch, particularly for computer vision tasks including object detection, classification and tracking.
- Familiarity with relational database management systems (RDBMS) such as PostgreSQL and Microsoft SQL Server, and experience with vector databases.
- Experience in application software development across multiple platforms including Windows, Linux, mobile operating systems (iOS, Android) and embedded systems.
- Strong programming skills in Python, Java and C++, with experience in GPU‑accelerated computing using CUDA and TensorRT.
- Knowledge of edge computing platforms and hardware accelerators such as NVIDIA Jetson, Google Coral and ARM Cortex.
- Excellent written and spoken English communication skills, fluency in Chinese is a plus for effective interaction with Chinese‑speaking stakeholders.
Artificial Intelligence (AI) Engineer in London employer: Consortium for Clinical Research and Innovation Singapore
Contact Detail:
Consortium for Clinical Research and Innovation Singapore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence (AI) Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field, attend meetups, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, GitHub contributions, or any relevant work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI-related questions and coding challenges. Practice explaining your thought process clearly, as communication is key when collaborating with cross-functional teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Artificial Intelligence (AI) Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your relevant experience, especially with machine learning frameworks like TensorFlow and PyTorch. We want to see how your skills align with our needs!
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 background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any cool AI projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see what you've done and how you approached challenges.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Consortium for Clinical Research and Innovation Singapore
✨Know Your AI Stuff
Make sure you brush up on the latest AI technologies and frameworks like TensorFlow and PyTorch. Be ready to discuss your hands-on experience with machine learning models, especially in real-world applications. This will show that you're not just familiar with theory but can actually apply it.
✨Showcase Your Collaboration Skills
Since the role involves working closely with cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any Agile methodologies you've used and how they contributed to project success. This will demonstrate your ability to work well in a team environment.
✨Prepare for Technical Questions
Expect some technical questions related to data pipelines, model training, and debugging. Brush up on your coding skills in Python, Java, and C++. You might even be asked to solve a problem on the spot, so practice coding challenges beforehand to keep your skills sharp.
✨Communicate Clearly
Strong communication skills are key, especially when presenting insights to stakeholders. Practice explaining complex concepts in simple terms. If you speak Chinese, mention it! It could give you an edge in communicating with Chinese-speaking team members or clients.