At a Glance
- Tasks: Join our team to build cutting-edge generative systems for video and audio synthesis.
- Company: Dynamic tech company at the forefront of machine learning innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make a real impact in the exciting field of generative AI and mentor future engineers.
- Qualifications: Experience in deploying ML systems and proficiency in Python and deep learning frameworks.
The predicted salary is between 70000 - 90000 £ per year.
We are looking for a Machine Learning Engineer to join our team and help build state‑of‑the‑art generative systems for video and audio synthesis, performance transfer, and visual translation. This role is hands‑on and technical, requiring experience in training and deploying deep learning models, a solid engineering mindset, and the ability to work cross‑functionally with research, product, and creative teams. As a senior member of the team, you’ll shape core infrastructure, set best practices, communicate with stakeholders, and mentor junior engineers while delivering high‑quality ML pipelines in production environments.
Must Haves
- Proven track record of deploying ML systems in production.
- A strong understanding of Machine Learning fundamentals.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
- Experience with training diffusion, transformer, or generative video models.
- Proficiency in Python.
- Experience building and maintaining scalable infrastructure (AWS, GCP, or custom solutions).
- Familiarity with CI/CD workflows, testing, and development best practices.
- Ability to mentor junior engineers and work independently.
Nice to Have
- Prior experience in generative AI for video, audio, or multimodal content.
- Experience with performance optimisation for ML models and pipelines.
- Background in computer graphics, real‑time rendering, or VFX pipelines.
- Open‑source contributions or published research in machine learning.
- Entrepreneurial mindset or experience working with startups or fast‑paced teams.
About You
- Innovative and solutions driven.
- Embrace challenges.
- Adaptable.
- Calm under pressure.
- Strong communication skills.
Machine Learning Engineer employer: DNEG Group
Join a forward-thinking company that values innovation and collaboration, where as a Machine Learning Engineer, you will have the opportunity to work on cutting-edge generative systems in a dynamic environment. Our culture fosters continuous learning and mentorship, providing you with ample opportunities for professional growth while working alongside talented teams in a vibrant location. Enjoy a supportive atmosphere that encourages creativity and offers competitive benefits, making it an ideal place for those seeking meaningful and rewarding employment.
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We think this is how you could land Machine Learning Engineer
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We think you need these skills to ace Machine Learning Engineer
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 DNEG Group. 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!
How to prepare for a job interview at DNEG Group
✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at DNEG Group!
✨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.
