ZoomInfo is the premiere provider of GTM solutions for revenue teams at businesses of all sizes. These solutions are built on a solid foundation of curated data on businesses and business professionals. As part of the ML architecture team, you will serve as an expert across machine learning, data sciences, and data/backend engineering, to guide the team on machine recognition, prediction, and information processing systems and platforms to organize and extract valuable insights at scale from rich and diverse datasets gathered from first, second, and third party sources.

Our Team Values

• Take pride in our contributions
• Support one another
• Optimize what matters
• Principled execution

What you’ll do:

• Contribute to building a platform to streamline all phases of data-centric innovation, including data organization, data access, data exploration, model prototyping, training, productionisation, testing, and ongoing monitoring of machine learning pipelines
• Design infrastructure, perform tool selection, implement utilities and automated workflows to facilitate the operations of a 40+ person, global data science organization
• Define cohesive processes and standards in conjunction with tools
• Document, communicate, and drive adoption of the ML platform, striving for operational excellence
• Collaborate with cross-functional teams to define project execution plans and support the productionisation, deployment, and integration of models and pipelines
• Hop into complex data science projects to provide expert guidance, design, and support
• Optimize machine learning and data transformation code for scale and robustness

What you’ll bring:

• 8+ years experience working with machine learning models and deploying them into production
• Degree in Computer Science, Electrical Engineering, Data Science, or other related computational fields
• Experience with NLP, computer vision, or deep learning frameworks such as Tensorflow, PyTorch, or HuggingFace, etc.
• Expert at Apache Spark, Databricks, Hadoop, or other big data systems
• Experience with machine learning frameworks such as Scikit-learn, SparkML, MLFlow, KubeFlow, etc.
• Experience with batch orchestration frameworks such as Airflow, or streaming services and systems
• Experience working with Cloud Platform Technologies in AWS, Google Cloud, or Azure
• Have a data-centric mindset and willingness to dive into data with methodical grace
• Strong communication skills, both oral and written, and ability to coordinate complex project execution with cross-functional teams
• Experience with Scala, Kafka, Apache Beam, Flink, Redis, Docker, or Kubernetes a plus
• Experience with recommender systems, entity extraction, or entity resolution a plus

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