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Experience andamp; qualificationsandlt;br or andgt; • Practical experience in the field of Machine Learning with experience developing and architecting software conversant with full lifecycle from prototype to production.andlt;br or andgt; • Technical know-how of AI or ML scenarios and operational challenges in production.andlt;br or andgt; • Applying engineering principles to develop and deploy ML models in medium to large scale environment.andlt;br or andgt; • Proven experience with machine learning offerings in the Google Cloud Platform. Cloud certifications .around Azure or AWS or GCP is a plus.. andlt;br or andgt; • Experience managing key elements of a data and ML platform: scalable data pipelines feature stores data lifecycle model store model deployment and monitoring ML pipelines.andlt;br or andgt; Career Level Years Of Expandlt;br or andgt; L7 10-14 yearsandlt;br or andgt; L8 7-10 yearsandlt;br or andgt; L9 4-7 yearsandlt;br or andgt; L10 2-4 yearsandlt;br or andgt; andlt;br or andgt; • Experience of deploying models in a production environment .knowledge of modern pipeline frameworks like Kubeflow or TensorFlow Extended .TFX.andlt;br or andgt; • A leader in exceptional software engineering practices including coding standards reviews testing and operations.andlt;br or andgt; • Strong experience in agile practices and CI or CDandlt;br or andgt; • Hands-on experience in development deployment and operation of data technologies and platforms such as:andlt;br or andgt; 1. Integration – APIs micro-services and ETL or ELT patterns andlt;br or andgt; 2. DevOps – Ansible Jenkins ELK andlt;br or andgt; 3. Version Control – Git Bitbucket native tools etc. andlt;br or andgt; 4. Containerization – Docker Kubernetes etc.andlt;br or andgt; 5. Orchestration – Airflow Cloud Composer Kubeflow etc.andlt;br or andgt; 6. Languages and scripting: Python Scala Java etcandlt;br or andgt; 7. Cloud Services – Google Cloud Platform and native toolsandlt;br or andgt; 8. Analytics and ML tooling – Vertex AI Sagemaker ML Studioandlt;br or andgt; 9. Execution Paradigm – low latency or Streaming batch and micro batch processing andlt;br or andgt; 10. Data platforms – Big Data .Dataproc Hadoop Spark Hive Kafka etc.. and Data Warehouse .BigQuery Teradata Redshift Snowflake etc.. andlt;br or andgt; 11. Visualization Tools – Looker PowerBI Tableauandlt;br or andgt; andlt;br or andgt; • Willingness and ability to learn quickly and apply creative thinking to finding great solutions and drive them to completion.andlt;br or andgt; • Experience working in a multi-disciplinary team where you enjoyed being the technical expert and enabling others.andlt;br or andgt; • Demonstrated ability to work with cross-functional IT or Data Science teams in a highly innovative and fast-paced environment.andlt;br or andgt; • Excellent verbal written and effective communication skills in English.andlt;br or andgt;
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