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aws python gcp mlops sagemaker📋 Description
- Lead Applied MLOps for production AI systems with focus on ground truth and evaluation.
- Architect annotation and measurement pipelines with human-in-the-loop and auto-annotation.
- Improve cost-efficiency via evaluation and model benchmarking for decisions.
- Enforce model-as-a-judge frameworks and deterministic PII scrubbing in production.
- Collaborate with DS and Engineering to integrate measurement loops in AWS/GCP.
- Balance model performance, latency, and cost in system design.
🎯 Requirements
- Annotation & Evaluation Expert: experience with Label Studio or similar tools.
- Applied MLOps Practitioner: production monitoring, versioning, evaluation loops.
- Python Proficiency: strong Python for glue code and API integrations.
- Model optimization mindset: balance performance, latency, and cost.
- Cloud & Infrastructure Fluency: AWS Sagemaker/S3 and GCP Vertex AI; DevOps collaboration.
- Collaborative Leader: help DS teams move faster with data/tools.
🎁 Benefits
- People: work with talented, collaborative teammates.
- Guidance: access to learning platform and training from day one.
- Meal stipends: remote-friendly meal stipends.
- Work/life harmony: 15 days vacation, holidays, wellness allowance, parental leave.
- Whole Health Package: medical, dental, vision, life, disability insurance, and more.
- Savings: 401k (USA) plan to help you plan ahead.
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