Google Cloud Platform AI Engineer

Google Cloud Platform AI Engineer

Posted 3 days ago by 1764055434

Negotiable
Outside
Remote
USA

Summary: The Google Cloud Platform AI Engineer role focuses on leveraging expertise in the Google Cloud Platform AI/ML ecosystem to build scalable and secure MLOps frameworks. The position requires proficiency in Python and various ML frameworks, along with a solid understanding of cloud architecture and data engineering. Strong communication skills are essential for collaboration with cross-functional teams. The role is remote and classified as outside IR35.

Key Responsibilities:

  • Strong hands-on expertise with Google Cloud Platform AI/ML ecosystem (Vertex AI, BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Run).
  • Proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and containerization (Docker, Kubernetes/GKE).
  • Good understanding of cloud architecture, microservices, event-driven patterns, and data engineering pipelines.
  • Experience building scalable, secure MLOps frameworks and CI/CD pipelines.
  • Excellent communication and collaboration skills for working with architects, stakeholders, and cross-functional teams.

Key Skills:

  • Strong hands-on expertise with Google Cloud Platform AI/ML ecosystem.
  • Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Experience with containerization (Docker, Kubernetes/GKE).
  • Understanding of cloud architecture and microservices.
  • Experience in building MLOps frameworks and CI/CD pipelines.
  • Excellent communication and collaboration skills.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Job Title: Google Cloud Platform AI Engineer
Location:Remote

  • Strong hands-on expertise with Google Cloud Platform AI/ML ecosystem (Vertex AI, BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Run).
  • Proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and containerization (Docker, Kubernetes/GKE).
  • Good understanding of cloud architecture, microservices, event-driven patterns, and data engineering pipelines.
  • Experience building scalable, secure MLOps frameworks and CI/CD pipelines.
  • Excellent communication and collaboration skills for working with architects, stakeholders, and cross-functional teams.

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