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
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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