Cloud Developer - ML/AI Focus

Strong hands-on experience with Google Cloud Platform (Google Cloud Platform) and cloud-native application development. Proficiency in Python for backend development, automation, APIs, and ML/AI application integration. Experience with Google Cloud Platform services including Cloud Run, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, and Vertex AI. Experience designing and developing scalable, secure, and highly available cloud applications. Strong understanding of REST APIs, microservices, event-driven architecture, and serverless computing. Hands-on experience integrating ML models, GenAI/LLM services, and AI APIs into cloud applications. Experience with CI/CD, Git, Docker, Kubernetes, and Terraform/IaC. Knowledge of Google Cloud Platform IAM, networking, security, monitoring, logging, and cost optimization. Experience working with Databricks and cloud-based data platforms is preferred. Ability to collaborate with Data Engineers, ML Engineers, Data Scientists, and Architects to deliver production-ready AI solutions.

Data Engineer - ML/AI Focus

Strong experience in data engineering and data pipeline development using Python and SQL. Hands-on experience with Databricks, Apache Spark, Delta Lake, Databricks Workflows, and notebooks. Strong knowledge of Google Cloud Platform data services, including BigQuery, Cloud Storage, Pub/Sub, and Dataflow. Experience designing and implementing scalable ETL/ELT batch and real-time data pipelines. Strong understanding of data modeling, data warehousing, data quality, governance, and data integration. Experience preparing and transforming large datasets for ML/AI and GenAI/LLM applications. Knowledge of feature engineering, feature pipelines, and ML data preparation is preferred. Experience implementing data pipeline orchestration, CI/CD, Git, testing, and monitoring. Strong understanding of cloud security, IAM, data privacy, and performance/cost optimization. Ability to work closely with Cloud Developers, ML Engineers, Data Scientists, and business teams to deliver reliable production data platforms.