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Senior Machine Learning Engineer

Build large-scale recommendation systems using embeddings for structured and unstructured data

Build and optimize recommendation systems, advanced NLP and embedding systems, and MLOps/LLMOps infrastructure. Utilize embeddings, graph-based structures, and vector databases to enhance recommendation quality and performance. Design and implement agentic systems for automated tasks and comprehensive evaluation frameworks.

Why This Role?

Directly contribute to building and optimizing AI systems that enhance customer engagement and data processing

Key Responsibilities

  • Build large-scale recommendation systems using embeddings for structured and unstructured data
  • Fine-tune and deploy embedding models for multi-language text understanding and semantic search
  • Architect and manage scalable MLOps and LLMOps infrastructure for model training, evaluation, and deployment

Requirements

  • Experience with recommendation systems and embeddings
  • Proficiency in advanced NLP and embedding models
  • Experience with MLOps and LLMOps infrastructure

Required Skills

machine learningpythonnlpmlopsllmopsrecommendation systemsvector searchNatural Language Processing

Indonesia Context

Working Hours Overlap:
Flexible — work your own hours
See remote (USD) vs local pay →

Keywords

Senior Machine Learning EngineerRecommendation SystemsNLPEmbedding ModelsMLOpsLLMOpsAI SystemsData Processing
View Original Description from Greenhouse Boards

Original description from Greenhouse Boards

<div class="content-intro"><p>ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast.</p></div><h2><strong>About the Applied AI Team</strong></h2> <p>The Applied AI team builds the intelligence layer that sits between ZoomInfo's high-quality data and the application and agentic layer through which customers engage. Using a product-led growth model, this team leverages customer engagement as input to build better recommendations, scoring, classification, and generative models.</p> <h2><strong>What you'll do:</strong></h2> <p><strong>Recommendation system</strong></p> <ul> <li>Build large scale recommendation systems utilizing embeddings generated for structured and unstructured data using methods such as a two tower architecture</li> <li>Performant recommendation designs which can scale to millions of recommendations per day for different product features</li> <li>Utilize graph based structures, search and scoring to enhance recommendation quality</li> </ul> <p><strong>Advanced NLP &amp; Embedding Systems</strong></p> <ul> <li>Fine-tune (LORA/PEFT), customize and deploy embedding models (LLMs/SLMs) for multi-language text understanding and semantic search</li> <li>Architect vector search solutions that enable language-agnostic clustering and classification across global datasets</li> <li>Build and optimize high-performance retrieval systems using vector databases</li> </ul> <p><strong>MLOps Lifecycle Management:</strong></p> <ul> <li>Architect and manage scalable MLOps and LLMOps infrastructure for robust model training, evaluation, deployment, and monitoring systems.</li> <li>Design comprehensive CI/CD pipelines, implement model monitoring frameworks to identify drift patterns, and ensure high availability and fault tolerance.</li> <li>Help establish metrics, experimentation frameworks, and statistical validation approaches for AI system performance</li> </ul> <p><strong>Agentic Workflows &amp; Evaluation</strong></p> <ul> <li>Design and implement agentic systems for automated web extraction, NER, and entity resolution tasks</li> <li>Build comprehensive evaluation frameworks for agent performance across data acquisition and processing workflows</li> <li>Create feedback loops that continuously improve agent decision-making and data quality outcomes</li> <li>Build, and scale MCP servers and integrate them into broader AI and product ecosystems</li> </ul> <p><strong>Cross-Functional Collaboration</strong></p> <ul> <li>End to end ownership of production workflows with close collaboration across engineering teams managing data, application, API and MCP layers to ensure models integrate seamlessly and scale with business needs</li> <li>Work with Product Management to translate business requirements into scalable ML solutions</li> </ul> <h2><strong>What you bring:</strong></h2> <ul> <li><strong>6+ years hands-on ML/NLP experience</strong> (or 3+ years post-PhD/Master's) with at least two delivered, revenue-impacting products in production environments</li> <li><strong>Expertise in modern AI architectures</strong> including transformer stacks, prompt engineering, RAG systems, vector-based information retrieval and context engineering</li> <li><strong>Proven track record building and managing production systems </strong>by architecting and deploying scalable distributed systems of REST &amp; MCP based microservices for applications and agents with observability and monitoring of latency, token utilization and system reliability</li> <li><strong>Strong applied research capabilities</strong> (PyTorch or TensorFlow) paired with software-engineering rigor (Python) and familiarity with open weight LLMs (QWEN, Gemma, OSS) and embedding models and vector search technologies (FAISS, Pinecone)</li> <li><strong>Executive communication skills</strong> with ability to persuade technical and non-technical audiences through data-driven storytelling, comfortable owning strategy, budget, and cross-functional collaboration</li> </ul> <p><strong>Utilize modern AI development tools</strong> (Claude Code, Codex, Cursor) in their engineering workflow to maximize development velocity and code quality.</p> <p>&nbsp;</p> <p>#LI-VC1</p> <p>#LI-Hybrid</p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process. We want our employees and their families to thrive.</p> <p>In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits <a class="c-link" href="https://www.zoominfo.com/careers#benefits" target="_blank" data-stringify-link="https://www.zoominfo.com/careers#benefits" data-sk="tooltip_parent">here</a>.</p></div><div class="title">Below is the US base salary for this position. Additional compensation such as Bonus, Commission, Equity and other benefits may also apply.</div><div class="pay-range"><span>$164,500</span><span class="divider">&mdash;</span><span>$258,500 USD</span></div></div></div><div class="content-conclusion"><p><strong>About us:</strong>&nbsp;</p> <p>ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller.</p> <p>ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant <a href="https://drive.google.com/file/d/1yiG-k0YX_sW10PiJk_xliDc3W-veJCrK/view?usp=drive_link" target="_blank">Privacy Notice</a> for more details on how we handle your personal information.</p> <p>ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available <a href="https://www.zoominfo.com/legal/nyc-local-law-144-notice" target="_blank">here</a>.</p> <p>ZoomInfo is proud to be an equal opportunity employer, hiring based on qualifications, merit, and business needs, and does not discriminate based on protected status. We welcome all applicants and are committed to providing equal employment opportunities regardless of sex, race, age, color, national origin, sexual orientation, gender identity, marital status, disability status, religion, protected military or veteran status, medical condition, or any other characteristic protected by applicable law. We also consider qualified candidates with criminal histories in accordance with legal requirements.</p> <p>For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. ZoomInfo does not administer lie detector tests to applicants in any location.</p></div>

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Company
ZoomInfo
Source
Greenhouse Boards
Job Type
full time
Location
Remote · Open worldwide
Category
Seniority
senior
Posted
Jun 9, 2026

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