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- Tasks: Design and enhance AI-driven document generation systems using cutting-edge technology.
- Company: Join a forward-thinking company at the forefront of AI innovation.
- Benefits: Enjoy hybrid work options and a collaborative environment with great perks.
- Why this job: Be part of a dynamic team shaping the future of AI and machine learning.
- Qualifications: Strong background in AI, NLP, Python, and cloud deployment required.
- Other info: Opportunity to work with advanced technologies like LLMs and Neo4j.
The predicted salary is between 48000 - 72000 £ per year.
We are seeking a highly skilled AI Engineer to design, develop, and enhance AI-driven document generation systems using large language models (LLMs) and traditional machine learning algorithms. The ideal candidate will have expertise in AI, natural language processing (NLP), and Python programming, with hands-on experience in generative AI, cloud deployment, and CI/CD pipelines. This role requires proficiency in Streamlit, knowledge of Neo4j, RDF, or OWL, and experience working with Azure cloud services.
Key Responsibilities
- AI & Machine Learning Development: Design, implement, and optimize AI-powered document generation systems using LLMs and ML models.
- NLP & Data Processing: Develop NLP-driven applications for text generation, summarization, and extraction.
- Cloud Deployment & Infrastructure: Deploy AI models and applications on Azure, ensuring scalability and reliability.
- Application Development: Build and maintain interactive AI applications using Streamlit.
- Knowledge Graphs & Semantic Technologies: Work with Neo4j, RDF, or OWL for knowledge representation and data modeling.
- CI/CD & MLOps: Implement CI/CD pipelines to automate model training, testing, and deployment.
- Collaboration & Best Practices: Work closely with cross-functional teams to integrate AI solutions into business workflows.
Required Qualifications & Skills
- Strong experience in AI, NLP, and machine learning algorithms.
- Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Hands-on experience with generative AI and LLM fine-tuning.
- Experience deploying AI applications on Azure (e.g., Azure ML, Azure Functions, Azure DevOps).
- Proficiency in Streamlit for building interactive AI applications.
- Knowledge of Neo4j, RDF, OWL, and semantic data technologies.
- Experience with CI/CD pipelines and MLOps for AI model deployment.
- Strong problem-solving and analytical skills with a focus on scalable AI solutions.
Senior ML/AI Engineer employer: RED Global
Contact Detail:
RED Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML/AI Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in generative AI and large language models. This will not only boost your confidence during interviews but also help you engage in meaningful discussions about the technologies we use at StudySmarter.
✨Tip Number 2
Get hands-on experience with Azure cloud services if you haven't already. Consider building a small project that involves deploying an AI model on Azure, as this practical knowledge will be invaluable when discussing your capabilities with us.
✨Tip Number 3
Brush up on your skills with Streamlit and consider creating a demo application. Showcasing your ability to build interactive AI applications can set you apart from other candidates and demonstrate your practical expertise.
✨Tip Number 4
Network with professionals in the AI and ML community, especially those who have experience with Neo4j, RDF, or OWL. Engaging in discussions or attending meetups can provide insights and potentially lead to referrals, making it easier for you to land a role with us.
We think you need these skills to ace Senior ML/AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI, NLP, and machine learning. Include specific projects where you've used large language models, Python, and any relevant frameworks like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and detail how your skills align with the job requirements. Mention your hands-on experience with generative AI and cloud deployment, particularly on Azure.
Showcase Relevant Projects: If you have worked on projects involving Streamlit, Neo4j, or CI/CD pipelines, be sure to include these in your application. Provide links to your work or GitHub repositories if possible.
Highlight Collaboration Skills: Since the role involves working closely with cross-functional teams, emphasise your teamwork and collaboration experiences. Mention any specific instances where you integrated AI solutions into business workflows.
How to prepare for a job interview at RED Global
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AI, NLP, and machine learning algorithms in detail. Highlight specific projects where you've used Python, generative AI, or deployed applications on Azure, as this will demonstrate your hands-on expertise.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Be ready to explain your thought process when tackling complex problems, especially those related to AI model optimisation and deployment. Use examples from your past work to illustrate your approach.
✨Familiarise Yourself with Relevant Technologies
Make sure you understand the tools and technologies mentioned in the job description, such as Streamlit, Neo4j, and CI/CD pipelines. Being able to discuss how you've used these technologies in previous roles will set you apart from other candidates.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with cross-functional teams, be ready to discuss your experience in collaboration. Share examples of how you've integrated AI solutions into business workflows and how you communicate technical concepts to non-technical stakeholders.
