Job description
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
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.