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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and scaling large-scale data systems and pipelines for machine learning workflows, with a strong focus on video generation models and post-training research. Proficient in cloud-based data storage and orchestration tools, ensuring efficient data processing and model improvement.
Highest-signal resume keywords
Large-Scale Data SystemsDistributed Data Processing FrameworksContainerization and OrchestrationCloud-Based Data StorageResearch in Generative Models
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonPyTorchJAXPySparkRayAirflowKubernetesDockerFFmpegOpenCV
Soft Skills
Independent ResearchProject Management
Tools & Technologies
AWSGCSAzureDALIVideo Processing Tools
Industry Keywords
Video Generation ModelsPost-Training ResearchData PipelinesWorkflow OrchestrationReward Modeling
Tech Stack
Tools & technologiesAirflowAWSAzureCloudDockerFFmpegKubernetesPySparkPythonPyTorchRay
About the role
Key responsibilities & impact- Drive foundational research on video generation models and post-training research
- Build and maintain scalable systems for ingesting, preprocessing, and delivering large-scale video data for model training
- Design and scale distributed data pipelines for preprocessing, dataset generation, and repeated dataset refreshes
- Own workflow orchestration, job scheduling, monitoring, and failure recovery for large-scale data processing jobs
- Implement and maintain containerized pipeline infrastructure using Kubernetes or equivalent orchestration systems
- Optimize cloud-based data storage and movement across AWS, GCS, and Azure for cost, throughput, and operational efficiency
- Define best practices for dataset storage layout, versioning, caching, retention, and access patterns
- Build tooling for large-scale deduplication workflows, including near-deduplication pipelines over video corpora
- Research and develop distillation methods for diffusion and flow-based video generation models
- Develop reward models and preference-based fine-tuning pipelines aligned with human judgments on aesthetics, motion quality, and prompt adherence
- Analyze relationships between base model behavior and post-training outcomes
- Collaborate with data, infrastructure, adjacent modeling, and foundation model teams to translate research into durable model improvements and inform pretraining decisions
Requirements
What you’ll need- Strong hands-on experience building or scaling large-scale data systems or pipelines for machine learning workflows
- Experience with distributed data processing frameworks such as PySpark or Ray, and orchestration tools such as Airflow or equivalent
- Familiarity with containerization and container orchestration, including Docker and Kubernetes
- Experience with cloud-based data storage and compute using AWS, GCS, and/or Azure
- Familiarity with video and media processing tools such as FFmpeg, PyAV, DALI, or OpenCV
- Familiarity with multimodal or media data, including video, image, text, and audio
- Strong research background in post-training methods for large-scale diffusion or flow-based generative models
- Deep hands-on experience in distillation across inference efficiency and quality preservation
- Experience with reward modeling or preference-based fine-tuning for generative models, including RLHF, DPO, or equivalent alignment approaches
- Solid understanding of the interplay between pretraining and post-training
- Proficiency in Python and modern machine learning frameworks, with a strong preference for PyTorch or JAX
- Track record of independent research and ability to drive projects from initial idea through experimental validation
- Publications at top-tier venues preferred
- Good understanding of reliable, scalable, and reproducible machine learning data workflows
Benefits
Comp & perks- Competitive salary and generous company equity
- Personal time off and paid holidays
- Health insurance
- Global travel insurance covering international travel
- Monthly spending stipend: $500 (~S$635)
- All equipment needed for your home office