At a Glance
- Tasks: Own the full stack of ML systems from data ingestion to production inference.
- Company: Fast-growing AI startup revolutionising filmmaking tools.
- Benefits: Attractive salary, equity, and hybrid work model in London.
- Other info: Exciting growth opportunities in a well-funded, innovative environment.
- Why this job: Join a cutting-edge team and shape the future of film technology.
- Qualifications: Strong Python backend skills and experience in building ML infrastructure.
The predicted salary is between 60000 - 80000 £ per year.
The opportunity for 2026 with a fast-growing start-up. EA are excited to be appointed to help in working with this AI start-up that is revolutionising tools that let filmmakers edit, localise, and refine performances without reshoots.
The Senior ML Systems Engineer will own the full stack from data ingestion through to distributed training and production inference. Importantly, a track record of building ML infrastructure or data platform is required.
- Strong Python backend expertise
- Data platform
- Training infrastructure
- TB-scale video, embedding, and metadata datasets
It's a hybrid role, with a London office, combining a very attractive and competitive salary, and equity. The company is at a genuinely exciting stage, being well-funded, technically advanced, and building something that is at the leading edge of technology with a strong market presence already.
If the timing is right (or if it isn’t but you’re curious), contact immediately.
Machine Learning Engineer - Hybrid employer: Exec Assignments Ltd
Join a dynamic AI start-up that is at the forefront of innovation in filmmaking technology, offering a hybrid work environment in London. With a competitive salary, equity options, and a culture that fosters creativity and collaboration, this company provides exceptional growth opportunities for employees eager to make a meaningful impact in the industry. Be part of a team that values your expertise and encourages you to push the boundaries of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Hybrid
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at AI startups. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving Python and data platforms. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with distributed training and production inference, as these are key for the role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities, and applying directly can sometimes put you ahead of the competition.
We think you need these skills to ace Machine Learning Engineer - Hybrid
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML infrastructure and Python backend expertise. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re excited about this opportunity and how you can contribute to our mission of revolutionising filmmaking tools. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any cool ML projects or data platforms, make sure to mention them! We love seeing practical examples of your work, especially if they relate to video, embedding, or metadata datasets.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Exec Assignments Ltd
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your experience with building ML infrastructure and data platforms, especially in Python. They’ll want to see that you can talk the talk and walk the walk!
✨Showcase Your Projects
Prepare to share specific examples of projects you've worked on, particularly those involving TB-scale video and metadata datasets. Highlight your role in these projects and the impact they had. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand Their Vision
Research the company and its mission to revolutionise filmmaking tools. Understanding their goals will help you align your answers with what they’re looking for. Show genuine interest in how your skills can contribute to their exciting journey.
✨Ask Smart Questions
Prepare thoughtful questions about their technology stack, team dynamics, and future projects. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you. Remember, interviews are a two-way street!
