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- Tasks: Develop scalable Python applications and deploy machine learning models on cloud platforms.
- Company: Join a forward-thinking tech company focused on innovative AI solutions.
- Benefits: Enjoy fully remote work and competitive pay of £550 per day.
- Why this job: Be at the forefront of AI technology, collaborating with diverse teams to make an impact.
- Qualifications: Experience in Python, GCP, Azure, and machine learning is essential.
- Other info: This is a contract position offering flexibility and the chance to work with cutting-edge technologies.
The predicted salary is between 39600 - 66000 £ per year.
Truly unique new role to the market from one of the UK’s fastest growing tech firms, which is servicing some of the largest global companies and growing at an exciting rate.
We are looking for talented AI Engineers at Senior and Mid-level, with a strong interest or experience in designing, building, and deploying intelligent systems – with a strong focus on agentic AI. Whether you already have hands-on experience building agentic workflows or you’re deeply curious and eager to be involved in this space, we’d love to hear from you.
The role will involve working on impactful projects, influencing technical direction and helping shape how AI is applied. Importantly, everything is driven by R&D and AI innovation, focused on tackling the most challenging aspects of AI. You will work closely with product, engineering and data teams to turn cutting-edge machine learning and AI research into scalable, production-ready solutions.
This is a superb opportunity with a forward-thinking and expansive client, with candidates being considered from a variety of unique and diverse backgrounds.
Key Responsibilities:
- Design and implement AI systems using LLMs and agent-based architectures for production use.
- Build and maintain scalable data pipelines and model training workflows
- Build autonomous or semi-autonomous agents that can reason, plan, and take actions
- Evaluate, iterate, and improve AI system performance, safety, and reliability
- Experiment with frameworks for agentic AI
- Collaborate with product and engineering teams to turn ideas into production-ready AI features
- Stay up to date with the fast-moving AI/LLM ecosystem
Required Skills & Experience (A blend of):
- Strong experience with Python and common ML libraries (e.g. PyTorch, NumPy, Panda, TensorFlow, scikit-learn)
- Experience with LLMs and fine tuning (OpenAI, open-source models)
- Hands-on experience with agent frameworks (e.g. LangGraph, AutoGen, CrewAI, etc.)
- Experience deploying AI systems to production
- Experience deploying models into production environments
- Experience of data processing tools and databases (SQL, NoSQL, or big data frameworks)
- Commercial expertise building microservices
- Strong problem-solving skills and the ability to work independently
- Curiosity and enthusiasm for agentic AI, even if your experience is still evolving
- Comfortable working in fast-moving, experimental environments
The above is not exhaustive. Please forward your CV to lee.johnston@sandersonplc.com to discuss this requirement in more detail.
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Artificial Intelligence Engineer employer: Sanderson
Contact Detail:
Sanderson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning. Being able to discuss recent advancements or projects you've worked on can really impress during interviews.
✨Tip Number 2
Showcase your experience with Python and cloud platforms like GCP and Azure through practical examples. Prepare to discuss specific projects where you deployed machine learning models or built scalable applications.
✨Tip Number 3
Network with professionals in the AI field, especially those who work with cloud technologies. Engaging in relevant online communities or attending virtual meetups can help you gain insights and potentially referrals.
✨Tip Number 4
Prepare for technical interviews by brushing up on algorithms and data structures, as well as cloud infrastructure management. Practising coding challenges related to machine learning can also give you an edge.
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, GCP, Azure, and machine learning technologies. Use specific examples of projects you've worked on that demonstrate your skills in these areas.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about AI development and how your background aligns with the responsibilities listed in the job description. Mention any relevant projects or achievements that showcase your expertise.
Showcase Your Technical Skills: Include a section in your application that outlines your technical skills, particularly in developing scalable applications, deploying machine learning models, and working with cloud services. Be specific about the tools and technologies you have used.
Highlight Soft Skills: Don't forget to mention your soft skills, such as communication and collaboration abilities. Provide examples of how you've worked effectively in teams or adapted to new technologies in previous roles.
How to prepare for a job interview at Sanderson
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, GCP, and Azure in detail. Bring examples of projects where you've developed scalable applications or deployed machine learning models, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Tech Stack
Research the specific technologies and tools used by the company. Familiarise yourself with their approach to AI and cloud services, as this knowledge can help you tailor your responses and show that you're genuinely interested in the role.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Practice explaining your thought process when solving problems related to machine learning algorithms or cloud infrastructure, as this will highlight your analytical skills and ability to think on your feet.
✨Emphasise Collaboration and Communication
Since the role involves working with cross-functional teams, be ready to discuss your experiences collaborating with others. Share examples of how you've effectively communicated complex technical concepts to non-technical stakeholders, showcasing your soft skills.
