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 Originally posted on Himalayas