Related skills
docker aws sql python kubernetes📋 Description
- Own production ML pipelines, generative AI, and real-time data streams.
- Design, build scalable AI/data solutions on AWS and edge-cloud.
- Build real-time/batch data pipelines with Kafka and Kinesis.
- Collaborate with product/data science to embed AI in operations.
- Design LLM-based solutions with prompts, RAG, and vector search.
- Scale agentic AI systems coordinating data, reasoning, and actions.
🎯 Requirements
- 5-8 years in data/ML engineering with production systems.
- Strong Python and SQL skills; solid CS fundamentals.
- AWS data pipelines (ETL/ELT) and scalable model deployment.
- Real-time streaming with Kafka/Kinesis; low-latency processing.
- Docker and Kubernetes; containerized ML workloads.
- MLOps: CI/CD, monitoring, model lifecycle; Airflow.
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