At a Glance
- Tasks: Develop and deploy cutting-edge Generative AI models and applications.
- Company: Join a leading tech firm at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with potential for contract extension.
- Why this job: Be part of a transformative field and shape the future of AI technology.
- Qualifications: Strong programming skills in Python and experience with LLMs and MLOps.
The predicted salary is between 60000 - 80000 € per year.
Role: GEN AI
Type: 1 year Fixed Term Contract (Chance for Extension)
Location: London / Dublin / Belfast
Core AI/ML Foundations: Strong foundational knowledge in GenAI, Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
Generative AI & LLM Expertise: Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs. Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation. Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc. Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates. Hands-on experience with agentic framework-based use case implementation. Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features.
Programming & Data Engineering: Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex. Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools. Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval. Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing.
Deployment & MLOps: Hands-on experience deploying GenAI-based models to production environments. Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines. Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments.
Generative AI Engineer in London employer: Ubique Systems
As a leading innovator in the field of Generative AI, our company offers an exceptional work environment in vibrant cities like London, Dublin, and Belfast. We prioritise employee growth through continuous learning opportunities and a collaborative culture that encourages creativity and innovation. With competitive benefits and the chance to work on cutting-edge technology, we are committed to fostering a rewarding career for our team members.
StudySmarter Expert Advice🤫
We think this is how you could land Generative AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community on LinkedIn or at local meetups. 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 projects, especially those involving LLMs and RAG pipelines. 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 your technical knowledge and problem-solving skills. Practice common interview questions related to GenAI and MLOps, and be ready to discuss your hands-on experience with specific tools and frameworks.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Generative AI Engineer in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with Generative AI and LLMs in your application. We want to see your hands-on experience with tools like Google Gemini and OpenAI models, so don’t hold back!
Tailor Your Application:Customise your CV and cover letter to match the job description. Use keywords from the role, especially around RAG pipelines and MLOps, to show us you’re the perfect fit for the position.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate a well-structured application that makes it easy for us to see your qualifications and experience at a glance.
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. We can’t wait to hear from you!
How to prepare for a job interview at Ubique Systems
✨Know Your Generative AI Inside Out
Make sure you brush up on your knowledge of generative AI and large language models. Be ready to discuss your hands-on experience with tools like Google Gemini and OpenAI models, as well as your understanding of Retrieval-Augmented Generation (RAG) pipelines. Prepare examples of projects where you've implemented these technologies.
✨Show Off Your Programming Skills
Since strong programming proficiency in Python is a must, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot or discuss your experience with libraries like Pandas, NumPy, and TensorFlow. Practise coding challenges beforehand to boost your confidence.
✨Discuss Deployment and MLOps Experience
Be ready to talk about your experience deploying GenAI models into production. Highlight your understanding of MLOps principles and CI/CD tools like Jenkins or GitLab CI. Share specific examples of how you've established robust deployment pipelines in past projects.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and ability to implement generative AI solutions. Think through potential use cases and how you would approach them, especially regarding prompt engineering strategies and integrating AI with enterprise applications.
