Sr. Machine Learning Engineer - AI

Zoom; Seattle (WA); Hybrid; USD 157,440 - 236,200; Full time

Job summary

Zoom Communications, Inc. is seeking a Machine Learning Engineer to help design, implement, and optimize knowledge graph services and AI-powered search at scale.

You will deploy ML models in a microservice environment, collaborate with cross‑functional teams, and maintain documentation using Confluence, Zoom Docs, and LucidChart.

This role emphasizes robust data pipelines, security, and scalable architectures, with a hybrid/remote work approach across the U.S.

Qualifications

• Bachelor’s degree in CS or related field.
• 3+ years in document understanding pipelines.
• 3+ years deploying ML models in microservices with Docker/Kubernetes (AWS EKS).
• 3+ years evaluating external data for AI search/document understanding.
• 3+ years building metrics and monitoring for AI search pipelines.
• 3+ years data ingestion, preprocessing, transformation pipelines.
• 3+ years architecting ML workflows for knowledge graphs and search.
• 3+ years collaborating with cross‑functional teams.
• 3+ years optimizing knowledge graph algorithms.
• 3+ years researching ML/NLP/knowledge graphs.
• 3+ years developing AI‑driven search and ranking algorithms.
• 3+ years documenting AI search systems with Confluence/Zoom Docs/LucidChart.
• 3+ years routing requests to ML models and managing feature stores.
• 3+ years implementing auth and security (JWT, AWS KMS).
• Telecommuting allowed: may work anywhere in the U.S.

Responsibilities

• Architect and optimize large-scale ML workflows for knowledge graphs and search services.
• Deploy, monitor, and maintain ML models in a Docker/Kubernetes environment.
• Collaborate with engineers, PMs, and domain experts to define requirements.
• Maintain documentation for AI search systems using Confluence, Zoom Docs, and LucidChart.
• Develop business logic for routing requests to ML models and managing feature stores.
• Implement authentication and security for ML pipelines (JWT, KMS).
• Lead AI search pipelines design, including document understanding and retrieval.
• Develop performance metrics and monitoring for scalable, low-latency AI search.

Skills

Docker

Kubernetes

LLMs

Knowledge graphs

NLP

AI search

Cloud platforms

AsyncMQ

Python

Education

Bachelor's degree in CS or related field

Tools

Confluence

Zoom Docs

LucidChart

Docling

AWS EKS

ZCP

Job description

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 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.

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 approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.

Benefits

As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click Learn for more information.

About Us

Zoomies help people stay connected so they can get more done together. We set out to build the best collaboration platform for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.

We’re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Find room to grow with opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment.

Our Commitment

At Zoom, we believe great work happens when people feel supported and empowered. We’re committed to fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential. If you require an accommodation during the hiring process, let us know—we’re here to support you at every step.

We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law.

If you need assistance navigating the interview process due to a medical disability, please submit an Accommodations Request Form and someone from our team will reach out soon. This form is solely for applicants who require an accommodation due to a qualifying medical disability. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed.

Think of this opportunity as a marathon, not a sprint! We're building a strong team at Zoom, and we're looking for talented individuals to join us for the long haul. No need to rush your application – take your time to ensure it's a good fit for your career goals. We continuously review applications, so submit yours whenever you're ready to take the next step.

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