Posted:2 weeks ago|
Platform:
Remote
Full Time
Job Post :- AI/ML Engineer Experience - 4+ years Location - Remote Key Responsibilities: Design, build, and maintain ML infrastructure on GCP using tools such as Vertex AI, GKE, Dataflow, BigQuery, and Cloud Functions. Develop and automate ML pipelines for model training, validation, deployment, and monitoring using tools like Kubeflow Pipelines, TFX, or Vertex AI Pipelines. Work with Data Scientists to productionize ML models and support experimentation workflows. Implement model monitoring and alerting for drift, performance degradation, and data quality issues. Manage and scale containerized ML workloads using Kubernetes (GKE) and Docker. Set up CI/CD workflows for ML using tools like Cloud Build, Bitbucket, Jenkins, or similar. Ensure proper security, versioning, and compliance across the ML lifecycle. Maintain documentation, artifacts, and reusable templates for reproducibility and auditability. Having GCP MLE Certification is Plus Show more Show less
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Salary: Not disclosed
Salary: Not disclosed