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