| ML Engineer at Remote, Remote, USA |
| Email: [email protected] |
| ML Engineer Location: TX/FL/NJ Client: CTS -> VZ Need Verizon EX employees Leading the consolidation and implementation of new concepts and processes in areas including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile Serving as a subject matter expert regarding the latest industry knowledge to improve the organization's systems and/or processes related to Machine Learning, Deep Learning, Responsible AI, Gen AI, Natural Language Processing, Computer Vision and other AI practices. Setting the standards for datasets and data representation methods. Extending existing ML libraries and frameworks. Determining processes and standards for running machine learning tests and experiments. Designing, developing, testing, deploying, maintaining, and improving machine learning system software. Setting the strategy for ML/AI tools and processes, determining the future needs of the business. Partnering with stakeholders across various business units, Enterprise Architects, Governance, Legal Council, Security to define an overall plan for the Registry, model governance and model inventory tracking. You will need to have: Advanced knowledge of all aspects of Machine Learning processes, tools, systems. Deep understanding and hands on experience with ML Engineering techniques and tools including ML Models measurement techniques, real-time and batch AI processors. Hands on experience with modeling platforms and tools like Domino, Jupyter, H2O.ai, DataRobot, Conda, ML Flow Even better if you have one or more of the following: Deep understanding of and hands-on experience with Data wrangling, feature engineering and creating scalable Data pipelines. Experience with database technologies like NoSQL, RDBMS, Graph DBs (like Druid, Neo4J), Presto, Hive, MongoDB, Cassandra, PostgreSQL, Teradata. and others Experience with designing and implementing complex enterprise systems including logging, monitoring, scheduling, CI/CD pipelining, code repos Experience with Google Cloud Platform, AWS or other similar cloud solutions (GCP preferred) Proficient in Big Data Technologies, Data Transport (Pulsar/Kafka), Spark, Jupyter/ Python. Experience working with languages like Core Java, J2EE, JSP, Servlet, Node.js, Angular, Python, R, Scala, SQL, in UNIX/Hadoop environments Expertise with large containerized environments utilizing Kubernetes, Docker, APIGEE and strong understanding of cloud solutions Knowledge of Model Development & Management Lifecycle Knowledge of computing statistical significance, familiarity with Statistical Model measurements and metrics, ML and DL modelling and other data science techniques -- Keywords: continuous integration continuous deployment artificial intelligence machine learning user interface javascript rlang information technology Florida New Jersey Texas ML Engineer [email protected] |
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| Tue Aug 27 00:15:00 UTC 2024 |