Applied ML Engineer, Data
Tasks
- Build data pipelines for video generation models
- Build internal tools and automation for dataset preparation and monitoring
- Collect relevant video data
- Design annotation task and quality control
- Develop preprocessing filtering and parsing workflows
- Drive pipeline projects end-to-end
- Improve data quality across the pipeline
- Optimize preprocessing time and cost constraints
- Orchestrate annotation workflows
- Prepare and deliver datasets to training clusters
- Prepare training samples
- Profile and optimize inference scripts for preprocessing
- Train and evaluate supporting models for data filtering and quality assessment
- Validate labels
Perks/Benefits
- 401k retirement plan
- Company equity
- Company holidays
- Dental insurance
- Fertility support
- Lifestyle spending account
- Lunch and snacks
- Medical insurance
- One Medical membership
- Paid time off
- Parental leave
- Sick days
- Vision insurance
Skills/Tech-stack
AWS S3 | Amazon DynamoDB | Annotation Workflows | Data Filtering | Data Parsing | Data Pipelines | Data Preprocessing | Data Processing | Dataset curation | Deep learning | Distributed Systems | Distributed data | Distributed data processing | Inference Optimization | Kubernetes | Label Quality Assurance | Machine Learning | PyTorch | Python | Quality Assurance
Education
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