Senior, ML Engineer - VLM
Tasks
- Build distributed reproducible cloud pipelines
- Build offline dataset pipeline
- Collaborate with model team on dataset specifications
- Define dataset schemas and quality metrics
- Develop VLM-assisted auto labeling
- Generate reasoning grounded labels
- Lead and mentor engineers
- Mine and curate long tail scenarios
- Translate research into production data systems
- Validate and route model failures to re labeling
Perks/Benefits
- 401k employer match
- AD and D insurance
- Company-Paid Holidays
- Flex schedule
- Life insurance
- Paid medical dental and vision
- Paid vacation
Skills/Tech-stack
3D Object Detection | AWS Athena | AWS DynamoDB | AWS ECS | AWS Lambda | AWS S3 | AWS Step Functions | Amazon Web Services | Apache Arrow | Apache Spark | BEV | CI/CD | Computer Vision | Databricks | Deep learning | Dense Captioning | Depth Estimation | Docker | Evaluation | Experiment tracking | Git | GitHub Actions | Language Models | ML Pipeline | MLOps | MLflow | Model Registry | Object Detection | Object Tracking | Open Vocabulary Detection | Parquet | PyTorch | PyTorch Lightning | Python | Quality metrics | Ray | Semantic Embeddings | Semantic Search | Semantic Segmentation | Sensor fusion | Spark | Step Functions | Terraform | Vector Databases | Vision Language Models | Vision-language | Web Services | Weights and Biases | Zero Shot Recognition | Zero-Shot
Education
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