At a Glance
- Tasks: Join us as a Gen AI Engineer and shape the future of AI technology.
- Company: Dynamic tech company at the forefront of Generative AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Exciting chance to work in a collaborative environment with potential for contract extension.
- Why this job: Be part of groundbreaking projects using cutting-edge AI tools and technologies.
- 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.
Gen AI Engineer in London employer: Ubique Systems
As a Gen AI Engineer at our company, you will thrive in a dynamic and innovative environment that champions creativity and collaboration. Located in vibrant cities like London, Dublin, or Belfast, we offer competitive benefits, a supportive work culture, and ample opportunities for professional growth in the rapidly evolving field of AI. Join us to be part of a forward-thinking team that values your contributions and fosters your development in cutting-edge technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Gen AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Gen AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with LLMs and RAG pipelines. We love seeing hands-on experience, so make sure to highlight any cool applications you've built or contributed to.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of Python libraries and MLOps principles. We recommend practising common interview questions related to generative AI and be ready to discuss your past experiences in detail.
✨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’re always on the lookout for passionate candidates who are eager to dive into the world of Gen AI.
We think you need these skills to ace Gen AI Engineer in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your foundational knowledge in GenAI, ML, and all those fancy terms like NLP and LLMs. We want to see how your experience aligns with the role, so don’t hold back!
Be Specific About Your Experience:When you mention your hands-on experience with LLMs or RAG pipelines, give us the juicy details! Tell us about the projects you've worked on and the tools you've used. This helps us picture you in the role.
Tailor Your Application:Don’t just send a generic application. Tailor it to fit the job description. Use keywords from the listing to show that you understand what we’re looking for. It makes a big difference!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way to ensure your application gets into our hands directly. Plus, it shows you’re keen on joining us at StudySmarter!
How to prepare for a job interview at Ubique Systems
✨Know Your GenAI Inside Out
Make sure you brush up on your foundational knowledge in Generative AI, Machine Learning, and Natural Language Processing. Be ready to discuss specific models like Google Gemini or OpenAI's offerings, and share your hands-on experiences with them.
✨Showcase Your RAG Expertise
Since the role requires deep knowledge of Retrieval-Augmented Generation pipelines, prepare to explain your experience with advanced RAG techniques. Bring examples of how you've implemented these in past projects to demonstrate your practical skills.
✨Demonstrate Your Programming Prowess
Be ready to talk about your programming skills, especially in Python. Highlight your experience with libraries like Pandas, NumPy, and TensorFlow, and consider discussing a project where you integrated generative AI with enterprise applications.
✨Discuss MLOps and Deployment Strategies
Since deployment is critical for this role, prepare to discuss your experience with MLOps principles and CI/CD tools. Share specific examples of how you've built and maintained robust deployment pipelines for GenAI models.
