{"id":2119719,"url":"https://alion.io/job/zoom-sr-machine-learning-engineer-ai","title":"Sr. Machine Learning Engineer - AI","company":{"id":3099,"name":"Zoom Communications","domain":"zoom.com","url":"https://alion.io/company/zoom","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":75,"open_postings":11,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":134000,"max_usd":240000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":295},"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Amazon EKS","optional":false},{"name":"AWS","optional":false},{"name":"Confluence","optional":false},{"name":"Docker","optional":false},{"name":"Docling","optional":false},{"name":"Feature Store","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-07-30T00:00:00Z","employer_posted_date":"2026-07-30","last_verified_at":"2026-10-12T05:51:17Z","board_verified":true,"closed_at":null,"days_open":74,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":74},"description":"Immigration sponsorship is not available for this positionWhat you can expect:\nWe 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.\nResponsibilities: \nArchitect 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;\nDeploy, monitor, and maintain machine learning models (LLMs and agentic workflows) in a microservice environment using Docker, Kubernetes (AWS EKS), and internal platforms (ZCP);\nCollaborate with cross-functional teams of engineers, product managers, and domain experts to define requirements and implement scalable, production-ready Machine Learning services.\nMaintain comprehensive documentation for all AI search systems, workflows, and services using Confluence, Zoom Docs, and LucidChart;\nDevelop business logic for routing requests to Machine Learning models and managing feature stores;\nImplement advanced authentication and security mechanisms for Machine Learning pipelines, including asymmetric JWT and secure key management (AWS KMS, internal CSMS.\nWork with asynchronous, distributed messaging frameworks (AsyncMQ).\nOptimize knowledge graph algorithms for performance, scalability, and reliability.\nConduct research on cutting-edge Machine Learning, NLP, and knowledge graph techniques, evaluating external data sources to enhance search and document understanding capabilities;\nDevelop/maintain documentation, best practices, guidelines;\nMentor junior engineers and contribute to team knowledge-sharing, best practices, and internal technical guidelines;\nLead the design, development, and deployment of AI search pipelines, including document understanding and retrieval systems, using libraries such as Docling;\nEvaluate external data sources to enhance AI search/document understanding;\nDevelop performance metrics, monitoring systems, and optimizations for AI search pipelines to ensure scalability, efficiency, and low latency;\nDevelop and maintain AI-driven search and ranking algorithms for enterprise-scale information retrieval and RAG (Retrieval-Augmented Generation) systems;\nDesign and maintain data ingestion, preprocessing, and transformation pipelines for both structured and unstructured data, ensuring high data quality and reliability.\nWhat we're looking for:\nRequires 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:\n3 years of experience in design, development, and deployment of document understanding and processing pipelines;\n3 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);\n3 years of experience in evaluating external data sources to enhance AI search/document understanding;\n3 years of experience in developing performance metrics, monitoring systems, and optimizations for AI search pipelines to ensure scalability, efficiency, and low latency;\n3 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;\n3 years of experience in architect and optimizing large-scale Machine Learning workflows to process structured and unstructured data for knowledge graphs and search services;\n3 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;\n3 years of experience optimizing knowledge graph algorithms for performance, scalability, and reliability.\n3 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;\n3 years of experience developing and maintaining AI-driven search and ranking algorithms for enterprise-scale information retrieval and RAG (Retrieval-Augmented Generation) systems;\n3 years of experience maintaining comprehensive documentation for all AI search systems, workflows, and services using Confluence, Zoom Docs, and LucidChart;\n3 years of experience developing business logic for routing requests to Machine Learning models and managing feature stores.\n3 years of experience implementing advanced authentication and security mechanisms for Machine Learning pipelines, including asymmetric JWT and secure key management (AWS KMS, internal CSMS.\nTelecommuting work arrangement permitted: position may work in various unanticipated locations throughout the U.S. Position does not require domestic or international travel.\nZoom Communications, Inc.\n#LI-DNI\n#Ind0\nSalary Range or On Target Earnings:\nMinimum:\n$157,440.00Maximum:\n$236,200.00In 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.\nNote: Starting pay will be based on a number of factors and commensurate with qualifications & experience.\nWe also have a location based compensation structure; there may be a different range for candidates in this and other locations.\nWays of Working\nOur 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.\nBenefits\nAs 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.\nAbout Us\nZoomies 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.\nWe’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.\nOur Commitment\nAt 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.\nWe 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.\nIf 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.\nThink 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.\nOur interviews are supported by BrightHire, a tool that helps us create a consistent and thoughtful interview experience and may include recordings. 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