AI/ML Engineer

Job Title:
1. AI/ML Engineer
2. AI Platform Engineer

Location: NYC, NY (Hybrid Model)

Energy & Utility domain with experience in Google solutions.

AI/ML Engineer:

• Design and implement scalable ML models using GCP services such as Vertex AI, BigQuery ML, AutoML, and AI Platform.
• Build and maintain end-to-end ML pipelines using Vertex AI Pipelines, Kubeflow, and TensorFlow Extended (TFX).
• Collaborate with data scientists, data engineers, and product teams to translate business problems into ML solutions.
• Optimize model performance and manage model lifecycle including training, evaluation, deployment, and monitoring.
• Ensure reproducibility, scalability, and security of ML workflows using GCP-native tools.
• Integrate ML models into production systems using Cloud Functions, Cloud Run, or GKE.
• Apply MLOps best practices for CI/CD, versioning, and monitoring of ML models.

AI Platform Engineer:

• Design and implement AI/ML infrastructure using Vertex AI, Kubeflow, TensorFlow Extended (TFX), and Cloud AI Platform.
• Develop and maintain CI/CD pipelines for ML models using Cloud Build, Cloud Functions, and Artifact Registry.
• Automate model training, deployment, and monitoring workflows using Vertex AI Pipelines and Cloud Composer.
• Collaborate with data scientists and ML engineers to productionize models and ensure scalability and reliability.
• Manage infrastructure using Terraform, Deployment Manager, or other Infrastructure-as-Code (IaC) tools.
• Ensure compliance with security, privacy, and governance standards across AI/ML systems.
• Monitor and optimize performance of AI workloads on GKE, Cloud Run, or Cloud Functions.