Job Location: Mumbai
As a Google Cloud Platform .GCP. ML Engineer you are an expert engineer with an eye for AI. You will be required to develop a holistic understanding of the AI or ML solution you are building including transferring some of the software engineering best practices to the data science world. andlt;br or andgt; Having a deep understanding of the mathematical underpinnings of the Machine Learning algorithms is a must have as you will be required to know what algorithms are available and when and how to apply them. andlt;br or andgt;
Qualifications
Practical experience in the field of Machine Learning with experience developing and architecting software conversant with full lifecycle from prototype to production. Technical know-how of AI or ML scenarios and operational challenges in production. Applying engineering principles to develop and deploy ML models in medium to large scale environment. Proven experience with machine learning offerings in the Google Cloud Platform. Cloud certifications .around Azure or AWS or GCP is a plus.. 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.
knowledge of modern pipeline frameworks like Kubeflow or TensorFlow Extended .TFX.
A leader in exceptional software engineering practices including coding standards reviews testing and operations.
Strong experience in agile practices and CI or CD Hands-on experience in development deployment and operation of data technologies and platforms such as:
1. Integration – APIs micro-services and ETL or ELT patterns
2. DevOps – Ansible Jenkins ELK
3. Version Control – Git Bitbucket native tools etc.
4. Containerization – Docker Kubernetes etc.
5. Orchestration – Airflow Cloud Composer Kubeflow etc.
6. Languages and scripting: Python Scala Java etc
7. Cloud Services – Google Cloud Platform and native tools
8. Analytics and ML tooling – Vertex AI Sagemaker ML Studio9. Execution Paradigm – low latency or Streaming batch and micro batch processing
10. Data platforms – Big Data .Dataproc Hadoop Spark Hive Kafka etc.. and Data Warehouse .BigQuery Teradata Redshift Snowflake etc..
11. Visualization Tools – Looker PowerBI Tableau Willingness and ability to learn quickly and apply creative thinking to finding great solutions and drive them to completion.
Experience working in a multi-disciplinary team where you enjoyed being the technical expert and enabling others.
Demonstrated ability to work with cross-functional IT or Data Science teams in a highly innovative and fast-paced environment. Excellent verbal written and effective communication skills in English.
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