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We are looking for an experienced, talented and motivated AI&ML Engineer to lead AI Industrialization for Verizon. As a lead, you will provide technology leadership and drive technology discussions along with Enterprise Architecture, Data Science and Data Engineering teams. You will also serve 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. You will lead the charter to Industrialize AI/ML model development, feature engineering, Model validation, deployment and Model Observability in both Real Time and Batch setup.
Leading the study and transformation of data science prototypes
Researching, designing, and implementing appropriate ML algorithms and tools
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 be part of an industry wide community, staying on top of the latest and greatest technologies to ensure an outside perspective is brought into Verizon. We're looking for someone who will define best practices in architecture to operate at an enterprise scale. Additionally, you will work with leadership and help align on strategies by defining a blueprint for ML Ops and come up with high-level design to implement solutions.
You will need to have:
Bachelor's degree or four or more years of work experience.
Four or more years of relevant work experience.
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
Business domain knowledge such as churn management, personalization, upsell/cross sale of Verizon products
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 modeling and other data science techniques
Understanding of various algorithms
Scalable distributed training & compute platform.
Exposure to product-based development methodology is desirable.
If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.
In this hybrid role, you'll have a defined work location that includes work from home and a minimum eight assigned office days per month that will be set by your manager.
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We’re proud to be an equal opportunity employer - and celebrate our employees’ differences, including race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, and Veteran status. At Verizon, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion page to learn more.
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