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docker aws python kubernetes gcp📋 Description
- Lead design, deployment, and maintenance of ML infrastructure in production.
- Build end-to-end data pipelines: ingestion, preprocessing, training, and deployment.
- Collaborate with data scientists to optimize model performance for production use.
- Establish CI/CD pipelines for deployment and reproducibility.
- Design monitoring and alerting for model health and proactive issue resolution.
- Optimize architecture for scalability, reliability, and cost.
🎯 Requirements
- Bachelor's or Master's in CS/Engineering/Math or related field.
- 6+ years in MLOps, data engineering, and/or DevOps.
- Proficiency in Python; other languages optional.
- Experience with LLMs and LangChain, or similar tools.
- Cloud experience: AWS, GCP (Azure optional).
- Strong Docker and Kubernetes skills.
🎁 Benefits
- Remote environment - work from home with a global team.
- Self-managed PTO – take time off as you need.
- Flexible work hours for work-life balance.
- Culture of innovation and big ideas.
- Work in your own time zone.
- Newest MacBook or PC; setup fee $500.
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