Principal AI/ML Engineer

You want more out of a career. A place to share your ideas freely - even if they're daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love - driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together - lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the V Team Life.

Join Verizon as we continue to grow our industry-leading network to improve the ways people, businesses, and things connect. 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.- Designing, developing, and deploying end-to-end AI/ML solutions, including data pipelines, model training, deployment, monitoring, and optimization

• Deploying machine learning models - On Prem, Cloud and Kubernetes environments

• Creating and implementing data and ML pipelines for model inference, both in real-time and in batches.

• Architecting, designing, and implementing large-scale AI/ML systems in a production environment.

• 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.

• Setting the strategy for ML/AI tools and processes, determining the future needs of the business, and enhancing existing ML libraries and frameworks.

• Analyzing extensive and complex data sets to determine the most efficient methods for processing large volumes of data using Spark, Hive, and SQL.

• Monitor the performance of data pipelines and make improvements as necessary

You are good with numbers and you love to dig into data to find the story. You are detail-oriented and know how to passionate about what really matters. You understand the importance of accuracy in data analytics and reporting. You are a self-starter and a multitasker who can work independently under tight timelines. You want to make an impact by providing the data that will help improve the experience of our customers.

You will need to have:

• Bachelor's degree or four or more years of work experience.

• Six or more years of relevant work experience.

• Strong experience in Spark/Hive/SQL, including hands-on experience building and deploying large volume data pipelines

• Proficiency in Python, Scala, SQL PySpark, Kafka, use of scheduling tools, Devops using Jenkins

• Experience cloud computing platforms (e.g., AWS, Azure, GCP) and their AI/ML services

• 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

Even better if you have one or more of the following:

• A degree in Computer Science, Engineering or related field.

• Six or more years of Enterprise Architecture or platform management.

• Hands-on experience with modeling platforms and tools such as and tools like Domino, Jupyter, H2O.ai, DataRobot, Conda, ML Flow

• Advanced skills in programming in Python, Java, and Git using Open Source tools like Spark, Flink and Jupyter Notebook.

• Knowledge of Development Lifecycle Management, DevOps Automation methods and practices, Post-Production Model Monitoring and End-to-End Architecture.

• Ability to run workloads over multiple nodes.

• Knowledge of data administration practices and approaches for data collection and ingest using Open Source tools such as Logstash and Kafka in a Hadoop ecosystem.

• Advanced knowledge of data science concepts and applied knowledge of practices and methods.

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.

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status, disability or other legally protected characteristics.