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aws python mlops model evaluation sagemaker📋 Description
- Architect annotation & measurement pipelines with human-in-the-loop workflows.
- Drive cost efficiency via model evaluation benchmarks.
- Enforce MLOps standards: monitoring, versioning, PII scrubbing.
- Collaborate on model strategy to improve product outcomes.
- Build & integrate measurement loops in AWS/GCP infrastructure.
🎯 Requirements
- Annotation & evaluation expertise with Label Studio/Scale AI.
- Applied MLOps with monitoring, versioning, evaluation loops.
- Python proficiency for glue code and API integrations.
- Model optimization mindset: trade-offs between performance, latency & cost.
- Cloud & infrastructure fluency: AWS Sagemaker/S3 and GCP Vertex AI.
- Collaborative leader enabling DS teams to move faster.
🎁 Benefits
- Talented, collaborative team of people.
- Guidance: learning platform and onboarding support.
- Work-life harmony: 25 days vacation, floating holidays, wellness allowance, parental leave.
- Stock options as part of our equity-sharing program.
- Healthcare coverage, including mental health, dental, vision.
- Comprehensive perks: wellness stipends, device and home office setup, meals.
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