Senior ML Systems Engineer

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 ❤️