Flawless
Technology
Senior/Staff/PrincipalMLSystemsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior / Staff / Principal ML Systems Engineer at Flawless. Skills: ML Systems Engineering, Data Platforms, Training Infrastructure, Production Inference. Build and evolve data platforms. Curate and manage datasets”
Industry & Context.
Problem-solving; Debugging
What They're Looking For.
Must Have
Python engineering skills, Experience building production services, Experience working with large-scale datasets, Experience with high-throughput data processing pipelines, Debugging skills, Problem-solving skills, Systems design skills, Experience collaborating effectively with cross-functional teams
Nice to Have
Experience building ML infrastructure, Experience building ML platforms, Experience building data platforms, Experience building large-scale backend systems, Experience with PyTorch, Experience building distributed systems, Familiarity with modern data storage technologies, Familiarity with analytics technologies, Familiarity with columnar data formats, Familiarity with data lake architectures, Experience working with video, Experience working with media, Experience working with multimodal ML pipelines, Familiarity with embeddings, Familiarity with vector search, Familiarity with retrieval systems, Experience operating production inference systems, Frontend experience (React or similar)
What You'll Do.
Build and evolve data platforms
Curate and manage datasets
Design systems to process videos
Optimize data storage patterns
Optimize data access patterns
Improve data ecosystem reliability
Improve data ecosystem scalability
Improve data ecosystem observability
Build and optimize training infrastructure
Improve training performance
Scale data loading workflows
Scale preprocessing workflows
Scale training workflows
Ensure training pipelines reproducible
Ensure training pipelines efficient
Ensure training pipelines easy to operate
Develop systems for model outputs
Build tooling for dataset exploration
Build tooling for experiment tracking
Build tooling for model comparison
Enable scientists to iterate rapidly
Maintain robust evaluation practices
Design infrastructure for model versioning
Maintain infrastructure for model validation
Maintain infrastructure for model deployment
Improve ML lifecycle reproducibility
Improve ML lifecycle governance
Support model promotion
Build inference infrastructure
Optimize inference infrastructure
Define model serving protocols
Improve model deployment patterns
Enhance inference system performance
Enhance inference system reliability
Enhance inference system scalability
Provide technical leadership
Drive architectural decisions
Mentor other engineers
Influence infrastructure strategy
How You'll Work.
Team & Collaboration
Cross-functional teams; Platform teams; Scientists; Machine learning engineers
Full Job Description
"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'RE BUILDING Research Services builds the infrastructure that enables scientists to train, evaluate, and deploy models at scale - forming the foundation of Hollywood's AI transformation. Our team sits at the intersection of large-scale data systems, machine learning, and high-performance computing. We own the full stack, from data ingestion and curation through distributed training and production inference, enabling researchers to move quickly while maintaining reliability and scalability. This role focuses on building and optimizing systems for large-scale multimodal datasets, including video, embeddings, and metadata, ensuring they are fast, reliable, and production-ready. THE ROLE We're looking for experienced ML Systems Engineers to join our Research Services team and help build the infrastructure that powers machine learning across Flawless. This role is open across multiple levels, from Senior Engineer through Staff Engineer. The level and scope of responsibility will be determined based on your experience, technical depth, leadership impact, and track record of delivery. As an ML Systems Engineer, you'll work closely with
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