At a Glance
- Tasks: Build and optimise ML systems for large-scale datasets in the film industry.
- Company: Flawless, an AI company revolutionising Hollywood with innovative technology.
- Benefits: Hybrid work, competitive salary, generous stock options, and a collaborative culture.
- Why this job: Join a creative team shaping the future of entertainment with ethical AI.
- Qualifications: Experience in ML infrastructure, strong Python skills, and familiarity with large datasets.
- Other info: Diverse perspectives are valued; apply even if you don't meet every requirement.
The predicted salary is between 60000 - 80000 £ per year.
The AI company that's revolutionizing Hollywood, Flawless is transforming Hollywood with assistive AI. Our tools empower filmmakers to edit, localize, and refine performances while preserving artistic intent. Designed to support, not replace, artists, our technology expands what is possible on screen and gives creators freedom to tell stories with greater impact and reach audiences in new ways. From enabling seamless multilingual releases to eliminating the need for costly reshoots, Flawless solves critical challenges that slow down productions and limit distribution.
We are also setting the standard for ethical AI in entertainment. Our Artistic Rights Treasury (A.R.T.) is a rights management solution that protects artists and rights holders, ensuring that innovation moves forward with transparency and respect for creative ownership.
What we are building: Research Services builds the infrastructure that enables scientists to train, evaluate, and deploy models at scale. Building the core of Hollywood AI transformation. The team sits at the cutting edge of data systems, machine learning, and high-performance compute—owning the full stack from data ingestion and curation through to distributed training and production inference. This role centers on building and optimizing systems for large-scale multimodal datasets (video, embeddings, metadata), making them fast, reliable, and ready for both research and production.
Your Impact:
- Data Platform for ML
- Build and evolve a data platform (LanceDB, DataFusion, SQL + vector search) used to curate large multimodal datasets
- Design systems that index and process thousands of videos using ML pipelines (face detection, quality assessment, tracking, etc.)
- Optimize data access patterns for training (Arrow, Parquet, Iceberg)
- ML Training Infrastructure
- Improve training performance across single-node and multi-node setups
- Work with PyTorch and Ray to scale data loading and training pipelines
- Ensure preprocessing and postprocessing pipelines are efficient and reproducible
- Evaluation & Experimentation Systems
- Build systems to collect, store, and analyze model outputs (Parquet / Iceberg)
- Develop tools for dataset inspection and model comparison (including video-based workflows)
- Model Registry & Lifecycle
- Design and maintain infrastructure for model versioning, experimentation, and promotion to production
- Inference Systems
- Own and optimize inference pipelines using Triton
- Define request protocols and build model ensembles
- Improve performance and reliability of production inference
You’ll Thrive here if:
- You have a track record of building ML infrastructure or data platforms—not just training models
- Strong Python backend expertise (e.g. FastAPI or similar)
- A deep intuition for data pipelines and performance trade-offs (I/O vs compute, batching, memory layout)
- Solid hands-on work with PyTorch (training pipelines, data loading, preprocessing)
- Practical experience with distributed systems (Ray, DDP, or similar)
- Proven ability to work with large-scale datasets (TB-scale or high-throughput pipelines)
- Familiarity with columnar data formats (Arrow, Parquet, Iceberg, or similar)
Nice to have:
- Exposure to video or media pipelines (FFmpeg, encoding, frame extraction)
- Familiarity with vector search or embedding systems
- Experience with Triton or production inference systems
- Frontend experience (React) for building internal tools
Why work at Flawless? You will be working in an environment based on trust, autonomy and collaboration, and this is a great opportunity for someone who wants to be part of a growing company in its most exciting stage of development. You can play a part in shaping the future of a company that’s caring, creative and collaborative. In addition to this, you'll also receive:
- Autonomy
- A hybrid working environment
- Competitive Salary
- All permanent employees receive generous stock options
I don’t meet all the listed requirements—should I still apply? Absolutely! Research shows that women and underrepresented groups often hesitate to apply unless they meet every qualification, but at Flawless, we actively work to break down those barriers. We believe diverse perspectives, experiences, and backgrounds make us stronger, and we are committed to supporting and elevating underrepresented talent. If you're excited about the role, share our values, and believe you can contribute meaningfully, we encourage you to apply—even if you don’t meet every single requirement. Your unique skills and perspective matter, and we’d love to hear from you ❤️
Senior ML Systems Engineer in London employer: Flawless AI
Contact Detail:
Flawless AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Systems Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Flawless. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or projects that highlight your ML infrastructure expertise, share them during interviews or networking events.
✨Tip Number 3
Prepare for technical challenges! Brush up on your Python and data pipeline knowledge. Be ready to discuss how you've tackled similar problems in the past.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior ML Systems Engineer in London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and its impact on the film industry shine through. We want to see how you connect with our mission of transforming Hollywood and supporting artists.
Tailor Your Experience: Make sure to highlight your relevant experience in building ML infrastructure or data platforms. We’re looking for specific examples that showcase your skills in Python, PyTorch, and working with large-scale datasets.
Be Authentic: Don’t be afraid to show your personality! We value authenticity and want to get to know the real you. Share your unique perspective and how it aligns with our values at Flawless.
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 our team!
How to prepare for a job interview at Flawless AI
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, PyTorch, and distributed systems. Brush up on your knowledge of data pipelines and performance trade-offs, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in building ML infrastructure or data platforms. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how you tackled complex problems effectively.
✨Understand Flawless' Mission
Familiarise yourself with Flawless’ vision of transforming Hollywood with AI. Be ready to discuss how your skills can contribute to their goals, particularly in ethical AI and supporting artists. This shows your alignment with their values and mission.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects, challenges they face, and how they measure success. This not only demonstrates your interest but also gives you a clearer picture of what working at Flawless would be like.