Senior Machine Learning Engineer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

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Verification

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Salary

$164K-$258K From the posting source checked Jun 20, 2026

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Machine Learning Engineer Remote 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. About the Applied AI Team 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. What you'll do: Recommendation system - Build large scale recommendation systems utilizing embeddings generated for structured and unstructured data using methods such as a two tower architecture - Performant recommendation designs which can scale to millions of recommendations per day for different product features - Utilize graph based structures, search and scoring to enhance recommendation quality Advanced NLP & Embedding Systems - Fine-tune (LORA/PEFT), customize and deploy embedding models (LLMs/SLMs) for multi-language text understanding and semantic search - Architect vector search solutions that enable language-agnostic clustering and classification across global datasets - Build and optimize high-performance retrieval systems using vector databases MLOps Lifecycle Management: - Architect and manage scalable MLOps and LLMOps infrastructure for robust model training, evaluation, deployment, and monitoring systems. - Design comprehensive CI/CD pipelines, implement model monitoring frameworks to identify drift patterns, and ensure high availability

Read the full description at www.zoominfo.com. FewerJobs shows a preview and links to the original posting.