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