Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexacorp, is seeking the following. Apply via Dice today! We are seeking a highly skilled **AI Engineer** with strong experience in **cloud-based AI/ML solutions** , preferably on **Google Cloud Platform (Google Cloud Platform)** . The ideal candidate will design, build, deploy, and scale machine learning and AI systems in a production cloud environment. **Key Responsibilities** - Design, develop, and deploy AI/ML models in cloud environments (Google Cloud Platform preferred; AWS/Azure acceptable) - Build end-to-end ML pipelines including data ingestion, feature engineering, training, evaluation, and deployment - Implement MLOps practices using CI/CD, monitoring, versioning, and model lifecycle management - Work with large datasets using cloud-native data services - Optimize model performance, scalability, and cost in cloud environments - Collaborate with data engineers, product teams, and stakeholders to translate business needs into AI solutions - Ensure security, compliance, and best practices in cloud AI implementations **Required Skills** - Strong experience as an AI Engineer / ML Engineer - Hands-on experience with Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage, Dataflow, Pub/Sub) - Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn) - Experience with REST APIs, microservices, and containerization (Docker, Kubernetes) - Solid understanding of ML algorithms, deep learning, and model evaluation - Experience with SQL and data processing frameworks **Good to Have** - Experience with AWS or Azure in addition to Google Cloud Platform - Knowledge of LLMs, GenAI, NLP, or Computer Vision use cases - Experience with Terraform / Infrastructure as Code - Exposure to real-time or streaming ML systems **Please Do Not Submit** - Pure Data Scientists with no production deployment experience - Candidates without cloud AI/ML implementation experience **Submission Requirements** Please ensure resumes clearly highlight: - Google Cloud Platform AI/ML project experience - Model deployment and MLOps responsibilities - End-to-end ownership of AI solutions