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- Tasks: Build innovative generative systems for video and audio synthesis using cutting-edge ML technologies.
- Company: DNEG, a leading visual effects company in Greater London with a collaborative culture.
- Benefits: Competitive salary, mentorship opportunities, and a dynamic work environment.
- Other info: Mentor junior engineers and collaborate with creative teams in an exciting workspace.
- Why this job: Join us to push the boundaries of innovation and shape the future of media.
- Qualifications: Experience in deploying ML systems, deep learning knowledge, and Python proficiency.
The predicted salary is between 60000 - 80000 £ per year.
DNEG in Greater London is seeking a Machine Learning Engineer to help build cutting-edge generative systems for video and audio synthesis. The ideal candidate will have experience deploying ML systems, a strong understanding of deep learning, and proficiency in Python.
You will work cross-functionally with research and creative teams, mentor junior engineers, and shape infrastructure as part of a collaborative environment. Join us to push the boundaries of innovation in a dynamic workspace.
Senior ML Engineer: Generative AI & Production Pipelines in London employer: DNEG
Contact Detail:
DNEG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer: Generative AI & Production Pipelines in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at DNEG or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got projects or contributions to open-source ML systems, make sure to highlight them. A portfolio speaks volumes and can set you apart from the crowd.
✨Tip Number 3
Prepare for the interview by brushing up on your deep learning concepts and Python skills. We recommend doing mock interviews with friends or using online platforms to get comfortable with technical questions.
✨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, it shows you're genuinely interested in joining the team.
We think you need these skills to ace Senior ML Engineer: Generative AI & Production Pipelines in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with deploying ML systems and deep learning in your application. We want to see how your skills align with the role, so don’t hold back!
Be Creative: Since we’re all about innovation, let your personality shine through in your written application. Use clear examples of your past work, especially in generative AI, to showcase your creativity.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the Senior ML Engineer role. We love seeing candidates who take the time to connect their experiences to what we’re looking for.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at DNEG
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially deep learning. Be ready to discuss your experience with deploying ML systems and any specific projects you've worked on that relate to generative AI.
✨Showcase Your Python Skills
Since proficiency in Python is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain your thought process while coding, so practice common algorithms and data structures.
✨Collaboration is Key
DNEG values teamwork, so be prepared to talk about how you've worked cross-functionally in the past. Share examples of how you've collaborated with research and creative teams, and how you’ve mentored junior engineers.
✨Be Ready for Innovation Discussions
This role is all about pushing boundaries, so think about how you can contribute to innovation. Prepare to discuss your ideas on future trends in generative AI and how you envision shaping infrastructure in a collaborative environment.