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- Tasks: Design and implement advanced algorithms for video quality analysis using cutting-edge machine learning techniques.
- Company: Join a renowned multinational company in the heart of London.
- Benefits: Competitive salary, immigration support, and global experience with a diverse team.
- Why this job: Make a real impact in video quality analysis while working with innovative technologies.
- Qualifications: Master's degree in Machine Learning or related field; programming experience in modern languages.
- Other info: Dynamic work environment with opportunities for professional growth and international exposure.
The predicted salary is between 36000 - 60000 £ per year.
We are thrilled to present an incredible career opportunity! We are recruiting on behalf of a renowned multinational company based in the United Kingdom, seeking a Machine Learning Engineer, Video Quality Analysis.
What you’ll do:
- As a key contributor, you will help develop innovative solutions by designing and implementing advanced algorithms to detect defects and evaluate overall video quality.
- This role involves leveraging the latest technologies, including foundational models, transformer‑based architectures, masked autoencoders, image processing, image analysis, computer vision, and machine learning.
- A primary focus will be on optimizing these algorithms to ensure they deliver accurate, efficient, and reliable results in near real‑time.
Key responsibilities:
- Develop detectors using advanced computer vision and machine learning (ML) techniques.
- Optimize solutions to ensure low latency and cost‑effective operation at scale for customers.
- Apply deep knowledge of the Machine Learning lifecycle, including model training, optimization, experimentation, and maintenance.
- Leverage core SDE computer science skills combined with a strong understanding of statistics and math to analyze algorithmic performance.
Requirements
Basic Qualifications:
- Experience contributing to the architecture and design (architecture, design patterns, reliability, and scaling) of new and current systems.
- Experience programming with at least one modern language such as Java, C++, or C# including object‑oriented design.
- Master's degree in Machine Learning, Applied Mathematics, Operations Research or a related field, or equivalent work experience.
Preferred Qualifications:
- Bachelor's degree in computer science or equivalent.
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Experience with developing and deploying Machine Learning Operations (MLOps) at scale.
- Experience with large‑scale foundational models and transformer‑based architecture (GenAI).
Benefits:
- Immigration support: The company provides support for your immigration process to the United Kingdom.
- Competitive salary: Enjoy a competitive salary package reflective of your skills and experience.
- Global experience: Gain international experience by working with a diverse team in a dynamic region.
Machine Learning Engineer, Video Quality Analysis in London employer: MENA Alliances
Contact Detail:
MENA Alliances Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, Video Quality Analysis in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and video quality analysis. We want to see your work in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practicing common ML algorithms and coding challenges. The more prepared you are, the more confident you’ll feel when it’s time to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for passionate individuals like you to join our team and make an impact in the world of machine learning.
We think you need these skills to ace Machine Learning Engineer, Video Quality Analysis in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with algorithms, computer vision, and any relevant projects that showcase your skills in video quality analysis.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background aligns with the company's goals. Don’t forget to mention specific technologies you’ve worked with!
Showcase Your Projects: If you've worked on any projects related to machine learning or video quality analysis, make sure to include them. We love seeing practical applications of your skills, so share links or descriptions of your work!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our amazing team!
How to prepare for a job interview at MENA Alliances
✨Know Your Algorithms
Brush up on the latest algorithms in video quality analysis and machine learning. Be ready to discuss how you’ve implemented these in past projects, especially focusing on optimising for low latency and reliability.
✨Showcase Your Coding Skills
Prepare to demonstrate your programming skills in languages like Java, C++, or C#. You might be asked to solve a coding problem on the spot, so practice common data structures and algorithms to ensure you're sharp.
✨Understand the ML Lifecycle
Familiarise yourself with the entire machine learning lifecycle, from model training to deployment. Be prepared to discuss your experience with MLOps and how you've maintained models in production.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to video quality analysis and their tech stack. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
