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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 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
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at DNEG. 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 a portfolio of projects or contributions to open-source, make sure to highlight them. We love seeing real-world applications of your expertise in ML and Python.
✨Tip Number 3
Prepare for technical interviews by brushing up on your deep learning concepts and coding skills. Practice common ML problems and be ready to discuss your past experiences in deploying systems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who want to innovate with us.
We think you need these skills to ace Senior ML Engineer: Generative AI & Production Pipelines
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 pushing boundaries, let your personality shine through in your written application. Share any unique projects or ideas you’ve worked on that relate to generative AI.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Senior ML Engineer role. We love seeing candidates who are genuinely interested in what we do.
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 code, so practice writing clean, efficient code that showcases your understanding of ML libraries.
✨Collaboration is Key
DNEG values teamwork, so be prepared to talk about your experience working cross-functionally. Share examples of how you've collaborated with research and creative teams in the past, and how you mentored junior engineers to foster a supportive environment.
✨Stay Innovative
This role is all about pushing boundaries, so come armed with ideas! Think about how you can contribute to innovation in generative systems and be ready to discuss your vision for future projects during the interview.