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aws tensorflow pytorch distributed systems mlops๐ Description
- Technical Leadership: set direction and standards for ML projects
- Mentorship & team development: mentor engineers and perform code reviews
- Hands-on work: contribute code, build PoCs, tackle high-risk challenges
- Architecture & design: design scalable ML architectures and systems
๐ฏ Requirements
- ML Engineering Excellence: deep ML across domains
- Production ML: production-grade ML systems
- Architecture & Design: scalable ML architectures
- MLOps: ML infra and operations
- LLM Systems: experience with LLM apps and RAG
- Frameworks: TensorFlow, PyTorch, scikit-learn
๐ Benefits
- Long-term B2B collaboration
- Fully remote setup
- A budget for your medical insurance
- Paid sick leave, vacation, public holidays
- Continuous learning support, including unlimited AWS certification sponsorship
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