Design, implement, and optimize the data infrastructure that supports AI and machine learning (ML) solutions
Ensure data availability, quality, and security
Ingest and transform data for the data lake and Feature Store
Develop and support the operationalization of AI and ML models
Conduct complex analyses and monitor data quality

Experience building optimized data pipelines for machine learning (ML) and artificial intelligence (AI) projects
Knowledge of ETL/ELT processes for ingesting large volumes of data for ML/AI applications
Languages: Python (required) and R (a plus)
AI/ML frameworks: TensorFlow, PyTorch, Scikit-Learn, MLflow
Scripting: Bash/Shell for workflow automation
Proven experience with Google Gemini
Proven experience with Google ADK
Demonstrated experience developing APIs in Python (minimum 3 years)
Experience with CI/CD and ML workflow automation tools such as MLflow, DVC, and Kubeflow
Familiarity with data monitoring and validation tools, Cloud Logging, Cloud Monitoring, Dynatrace, or Datadog
Airflow, Luigi, or Prefect for orchestrating ML/AI pipelines
Knowledge of SQL and NoSQL
Ability to manage Data Lakes for AI data preparation
Knowledge of Feature Stores
AWS: experience with S3, Glue, SageMaker, EC2, Lambda, and Redshift
GCP: experience with BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Run, Composer, Vertex AI, Cloud Functions, and Dataplex
Docker and Kubernetes for running and orchestrating AI/ML models
Knowledge of Terraform and CloudFormation
Implementation of automated pipelines for training, validation, deployment, and monitoring of AI models
Ability to understand business requirements and translate them into technical AI solutions

Senior AI Engineer, ADK GCP

Key skills