Cloud Developer – ML/AI Focus

Need Local Or Near By Consultant Who Can Attend Face - Face Interview

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.