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Job Description
Structured overview of role & requirementsAbout This Role
Design and optimize BigQuery SQL data pipelines for business insights including anomaly detection and IoT telemetry analysis.
Own end-to-end MLOps lifecycle for production ML models on GCP, including deployment, monitoring, and automated retraining pipelines.
Conduct evidence-based code reviews verifying logic against live data and enforce data quality governance across ML features and training datasets.
Minimum Requirements
5 to 8 years of overall experience with 3+ years hands-on BigQuery/SQL-at-scale and production ML systems.
Strong hands-on experience with BigQuery or similar cloud data warehouses and advanced SQL (CTEs, window functions, procedural SQL).
Deep ownership of MLOps on GCP (Vertex AI) or AWS including CI/CD, versioning, deployment automation, and monitoring.
Bachelor's or Master's degree in Computer Science, Data Science, or Artificial Intelligence from top-tier colleges.
Ideal Candidate Profile
Experienced in production-grade Python ML code with frameworks like scikit-learn, TensorFlow, or PyTorch for feature engineering and inference pipelines.
Demonstrates strong statistical modeling skills and ability to validate insights for statistical soundness and bias prior to stakeholder delivery.
Comfortable working cross-functionally to clarify ambiguous requirements and document technical rationale for asynchronous review.