| Looking for Machine Learning Engineer with Bigdata and GCP Need 9+ profiles. at Remote, Remote, USA |
| Email: [email protected] |
| From: Austin varma, Eminencets [email protected] Reply to: [email protected] Role : Machine learning with GCP Location : Remote Exp: 9+ Must Have Qualifications: Bachelors degree in Engineering or Computer Science or equivalent OR Masters in Computer Applications or equivalent. 7-10+ years of software development experience and leading teams of engineers and scrum teams 4+ years of experience in applying Statistics along with end to end ML engineering (design, development & implementation of end-to-end AI/ML models) Hands-on experience on writing and understanding complex SQL(Hive/PySpark-dataframes), optimizing joins while processing huge amount of data Good understanding of various AI/ML models including Classification, Clustering, Regression in detecting Product anomalies and building early warning systems Expertise with data structures, data modeling, and software architecture Good to have Qualifications: Expert on Hadoop and Spark Architecture and its working principle Experience in UNIX shell scripting Ability to design and develop optimized Data pipelines for batch and real time data processing Should have experience in analysis, design, development, testing, and implementation of system applications Demonstrated ability to develop and document technical and functional specifications and analyze software and system processing flows Aptitude for learning and applying programming concepts. Ability to effectively communicate with internal and external business partners. Preferred Additional: Experience in cloud platforms like GCP/AWS, building Microservices and scalable solutions is highly desired Knowledge of Financial reporting ecosystem will be a plus 2+ years of experience in designing and building solutions using Kafka streams or queues Experience with GitHub and leveraging CI/CD pipelines Experience with NoSQL i.e., HBase, Keywords: continuous integration continuous deployment artificial intelligence machine learning |
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| Tue Feb 13 20:00:00 UTC 2024 |