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nlp azure java docker aws📋 Description
- Own the end-to-end ML lifecycle: data ingestion, training, deployment, monitoring.
- Transition AI prototypes to production with CI/CD, automation, observability.
- Lead system design and ML infrastructure guidance.
- Develop AI-powered apps and inference services for performance and cost.
- Integrate LLMs, generative AI, and NLP into IMO Health products.
- Implement monitoring, logs, alerts, and dashboards for model quality.
🎯 Requirements
- 8+ years in software/AI engineering, building production systems.
- BS or MS in CS/Engineering or related field (or equivalent).
- Strong CS fundamentals: data structures, algorithms, OS, networking.
- Expert Python or Java with production-ready practices.
- Hands-on ML systems ownership: deployment, monitoring, retraining.
- Experience designing CI/CD, automation, and observability for ML.
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