At a Glance
- Tasks: Develop cutting-edge AI solutions for video, audio, image, and text content.
- Company: Join a leading global tech organisation at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with exciting projects and career advancement opportunities.
- Why this job: Make a real impact in AI-driven content intelligence and work with advanced technologies.
- Qualifications: Master’s or PhD in relevant fields and 5+ years of AI/ML experience required.
The predicted salary is between 70000 - 90000 £ per year.
We are currently partnered with a leading global technology organisation developing next-generation AI-driven content intelligence and recommendation systems. As part of their growing AI research and engineering team, they are looking to hire a Senior AI/ML Engineer to develop advanced multimodal understanding solutions across video, audio, image, and text using state-of-the-art Multimodal Large Language Models (MLLMs).
Key responsibilities
- Develop and optimise multimodal AI frameworks focused on semantic understanding, narrative reasoning, and high-level content interpretation
- Build and deploy advanced AI models combining video, audio, image and text signals
- Working with Multimodal Large Language Models (MLLMs), Vision Language Models (VLMs), and foundation models
- Develop scalable, low-latency AI systems suitable for high-concurrency production environments
- Collaborate with recommendation, search, and platform teams to integrate content intelligence signals into production pipelines
Key requirements
- Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- 5+ years of commercial experience in AI/ML research or advanced machine learning engineering
- Strong experience in at least two of the following areas:
- Computer Vision
- Natural Language Processing
- Recommendation Systems
- Hands-on experience with PyTorch, TensorFlow, or JAX
- Experience working with Large Language Models, Vision Language Models, or Multimodal LLMs
- Experience deploying machine learning models into large-scale production environments
Senior AI/ML Engineer – Multimodal Content Intelligence / MLLMs / Computer Vision / NLP in Edinburgh employer: European Tech Recruit
Join a pioneering global technology organisation that champions innovation and creativity in the AI space. With a strong commitment to employee development, you will have access to cutting-edge projects and collaborative work culture that fosters growth and learning. Located in a vibrant tech hub, this role offers unique opportunities to work with advanced AI technologies while enjoying a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI/ML Engineer – Multimodal Content Intelligence / MLLMs / Computer Vision / NLP in Edinburgh
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We think you need these skills to ace Senior AI/ML Engineer – Multimodal Content Intelligence / MLLMs / Computer Vision / NLP in Edinburgh
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at European Tech Recruit. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
