Lead AI/ML Engineer
Primary Skills
- Value Quantification : Pre-Model Development, Model Provisioning: Kubernetes, Kibana, Model Monitoring, Cloud Computing, Python/PySpark, SAS/SPSS, Great Expectation, Evidently AI, Deployment Strategies (A/B, Blue green, Canary), Model testing, Tools(KubeFlow, BentoML), Integration testing, ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Value Quantification: Post-Model Deployment, Model Experimentation, R/ R Studio
Specialization
- ML Engineering: AI/ML Engineer
Job requirements
- Skills Data Engineering: SQL, BigQuery, Apache Airflow Cloud: GCP (BigQuery, Dataflow), Programming: Python (data processing, basic scripting) and Java Data Handling: Data modeling, query optimization Roles and Responsibilities • Designed, developed, and optimized complex data pipelines to ingest, process, and store data from Google Cloud Storage (GCS) to BigQuery. • Built API-integrated workflows to fetch data from external APIs, process responses, and load results into downstream systems. • Implemented Pub/Sub–based event-driven pipelines supporting both real-time and batch data processing, including triggers and message handling. • Created and managed BigQuery DDLs, views, and authorized views, ensuring secure data access through appropriate roles and permissions. • Improved ETL pipeline and SQL query performance, reducing processing time and enhancing BigQuery warehouse efficiency. • Conducted DEV and UAT testing, validating business logic, data quality, and end-to-end pipeline stability. • Applied business transformation logic to convert raw data into analytics-ready datasets. • Generated weekly and monthly SQL-based reports and automated their distribution via email for business stakeholders. • Collaborated with client and business stakeholders to gather requirements and deliver accurate, efficient, and interpretable data solutions. • Developed interactive dashboards using Looker Studio to enable clear data visualization and reporting.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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