Overview
Skills
Job Details
Role 1: AI/ML Cloud Engineer (3 Positions)
Experience range: 10-15 years
Location: US (Remote)
Job Description:
Cloud Infrastructure: Build and manage compute, storage, and networking for AI/ML workloads using platforms like AWS, Azure, or Google Cloud.
MLOps/AIOps: Automate model deployment, monitoring, and retraining using tools like Kube Flow, MLflow, or SageMaker Pipelines. AWS (SageMaker, ECS, S3), Google Cloud (Vertex AI, BigQuery), Azure (AI Studio, Synapse) Python, TensorFlow, PyTorch, scikit-learn, Cursor Coding
Data Engineering: Set up data lakes, ETL pipelines, and real-time data processing systems for AI models.
Cost & Performance Optimization: Optimize GPU/TPU usage, autoscaling, and cloud resource management for high-efficiency AI systems.
Security & Compliance: Implement IAM, data encryption, and compliance policies for AI data and models.
Good to have primary Google cloud specific skill sets (including Enterprise Gemini AI experience)
Taras Technology, LLC is an EEO/AA Employer: women, minorities, the disabled and veterans are encouraged to apply