Data Engineer / MLOps Specialist
Role Summary
Build data pipelines and model-ops infrastructure that keep AI workloads reliable, compliant, and cost-efficient.
Key Responsibilities
• Ingest, transform, and version datasets with Databricks or Snowflake.
• Create CI/CD pipelines for ML using GitHub Actions and Terraform.
• Monitor model drift, latency, and resource usage with Prometheus & Grafana.
Must-Have Qualifications
• 4+ years in data engineering or DevOps.
• Kubernetes, Docker, and GPU orchestration skills.
• Proficiency in Spark or Flink.
Preferred
• Exposure to Ray Serve, KServe, or Sagemaker.
• Certifications: Azure Data Engineer, CKAD.
Engagement: Full-time contract, 612 months, remote with overlap to GMT+4.
Job Types: Full-time, Permanent
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