Sr. Machine Learning Engineer - AI

About this role

Immigration sponsorship is not available for this position What you can expect: We are seeking a highly skilled and motivated Machine Learning Engineer to join our team and play a key role in developing and maintaining our knowledge graph service. As a Machine Learning Engineer specializing in knowledge graphs, you will work closely with cross-functional teams to design, implement, and optimize algorithms and models that enable efficient representation, integration, and retrieval of structured and unstructured data. Responsibilities:    • Architect and optimize large-scale Machine Learning workflows to process structured and unstructured data for knowledge graphs and search services; Architect and optimize large-scale Machine Learning workflows to process structured and unstructured data for knowledge graphs and search services; • Deploy, monitor, and maintain machine learning models (LLMs and agentic workflows) in a microservice environment using Docker, Kubernetes (AWS EKS), and internal platforms (ZCP); • Collaborate with cross-functional teams of engineers, product managers, and domain experts to define requirements and implement scalable, production-ready Machine Learning services. • Maintain comprehensive documentation for all AI search systems, workflows, and services using Confluence, Zoom Docs, and LucidChart; • Develop business logic for routing requests to Machine Learning models and managing feature stores; • Implement advanced authentication and security mechanisms for Machine Learning pipelines, including asymmetric JWT and secure key management (AWS KMS, internal CSMS. • Work with asynchronous, distributed messaging frameworks (AsyncMQ). • Optimize knowledge graph algorithms for performance, scalability, and reliability. • Conduct research on cutting-edge Machine Learning, NLP, and knowledge graph techniques, evaluating external data sources to enhance search and document understanding capabilities; • Develop/maintain documentation, best practices, guidelines; • Mentor junior engineers and contribute to team knowledge-sharing, best practices, and internal technical guidelines; • Lead the design, development, and deployment of AI search pipelines, including document understanding and retrieval systems, using libraries such as Docling; • Evaluate external data sources to enhance AI search/document understanding; • Develop performance metrics, monitoring systems, and optimizations for AI search pipelines to ensure scalability, efficiency, and low latency; • Develop and maintain AI-driven search and ranking algorithms for enterprise-scale information retrieval and RAG (Retrieval-Augmented Generation) systems; • Design and maintain data ingestion, preprocessing, and transformation pipelines for both structured and unstructured data, ensuring high data quality and reliability.

What we're looking for: Requires a bachelor’s degree in computer science, Communications Engineering, a related field, or a foreign degree equivalent. Must have 3 years of experience in job offered or related occupation. Must have 3 years of experience in the following: • 3 years of experience in design, development, and deployment of document understanding and processing pipelines; • 3 years of experience in deploy, monitor, and maintain machine learning models (LLMs and agentic workflows) in a microservice environment using Docker, Kubernetes (AWS EKS), and internal platforms (ZCP); • 3 years of experience in evaluating external data sources to enhance AI search/document understanding; • 3 years of experience in developing performance metrics, monitoring systems, and optimizations for AI search pipelines to ensure scalability, efficiency, and low latency; • 3 years of experience in design and maintaining data ingestion, preprocessing, and transformation pipelines for both structured and unstructured data, ensuring high data quality and reliability; • 3 years of experience in architect and optimizing large-scale Machine Learning workflows to process structured and unstructured data for knowledge graphs and search services; • 3 years of experience collaborating with cross-functional teams of engineers, product managers, and domain experts to define requirements and implement scalable, production-ready ML services; • 3 years of experience optimizing knowledge graph algorithms for performance, scalability, and reliability. • 3 years of experience conducting research on cutting-edge Machine Learning, NLP, and knowledge graph techniques, evaluating external data sources to enhance search and document understanding capabilities; • 3 years of experience developing and maintaining AI-driven search and ranking algorithms for enterprise-scale information retrieval and RAG (Retrieval-Augmented Generation) systems; • 3 years of experience maintaining comprehensive documentation for all AI search systems, workflows, and services using Confluence, Zoom Docs, and LucidChart; • 3 years of experience developing business logic for routing requests to Machine Learning models and managing feature stores. • 3 years of experience implementing advanced authentication and security mechanisms for Machine Learning pipelines, including asymmetric JWT and secure key management (AWS KMS, internal CSMS. • Telecommuting work arrangement permitted: position may work in various unanticipated locations throughout the U.S. Position does not require domestic or international travel.

Zoom Communications, Inc. #LI-DNI #Ind0  

Salary Range or On Target Earnings:

Minimum: $157,440.00 Maximum: $236,200.00 In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.

Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.

We also have a location based compensation structure;  there may be a different range for candidates in this and other locations.

Ways of Working Our structured hybrid a

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