Senior Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval

The Ads Signals Intelligence team is seeking a hands-on and experienced Machine Learning Engineer to develop next-generation ML-driven signal platforms. This role focuses on building content understanding systems and large-scale infrastructure for near real-time signal updates, enabling smarter, privacy-aware decision-making. You will develop rich semantic signals from various sources to support scalable ad retrieval, creative ranking, and marketplace optimization, working with LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning.

Must Have

• Design, implement, and scale ML systems for semantic signals.
• Contribute to retrieval and ranking pipelines.
• Fine-tune and apply LLMs for NLP tasks.
• Construct and utilize knowledge graphs and entity linking systems.
• Work with multimodal data to build robust signal representations.
• Build core components for a content understanding platform.
• Own experimentation, offline evaluation, and online validation.
• Collaborate across engineering, infra, and product teams.
• 4+ years of experience in machine learning or applied research.
• Deep understanding of information retrieval, semantic search, and query-document matching.
• Strong hands-on experience with LLM fine-tuning, knowledge graph construction, and entity-centric modeling.
• Experience working with multimodal models.
• Proficiency in Python and ML frameworks like PyTorch, TensorFlow.
• Background in statistical modeling, optimization, and ML theory.
• Demonstrated ability to deliver high-impact ML solutions in production environments.
• Bachelor's in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field.

Good to Have

• Exposure to ad tech domains such as auction modeling, targeting, attribution, or creative optimization.

Perks & Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Range of discounted products and free services
• Reimbursement for certain educational expenses (including tuition) for career advancement
• Discretionary bonuses or commission payments
• Relocation assistance
• Opportunity to become a shareholder through employee stock programs

We focus deeply on our customers’ experience. Our Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Services, including the App Store, News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!

The Ads Signals Intelligence team is seeking a hands-on and experienced Machine Learning Engineer to develop the next generation of ML-driven signal platforms that power retrieval, prediction, and relevance across the advertising ecosystem—including the App Store and News. This role focuses on building content understanding systems and large-scale infrastructure capable of delivering near real-time signal updates, enabling smarter, privacy-aware decision-making throughout the ad delivery stack. This role focuses on developing rich semantic signals from a variety of sources—including queries, creatives, metadata, and user interactions—to support scalable ad retrieval, creative ranking, and marketplace optimization. You'll work at the forefront of LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning to extract structured intelligence from unstructured data. While ad tech knowledge is a strong bonus, the core of the role is building high-quality, privacy-centric signals that fuel some of the most advanced machine learning systems. As part of the Ads Signals Intelligence team, you’ll be shaping the foundation of ad ranking and relevance systems through world-class signal understanding. You’ll work on problems at the cutting edge of retrieval, multimodal learning, LLMs, and content intelligence—while contributing to the mission to deliver high-performing, privacy-first advertising experiences at scale.

• Design, implement, and scale ML systems that extract high-value semantic signals from structured and unstructured content
• Contribute to retrieval and ranking pipelines using techniques in query understanding, semantic embedding, and dense/sparse indexing
• Fine-tune and apply Large Language Models (LLMs) for NLP tasks like content labeling, rewriting, and semantic similarity
• Construct and utilize knowledge graphs and entity linking systems for enriching creative and query signals
• Work with multimodal data (e.g., combining text, image, and metadata signals) to build robust, cross-domain signal representations
• Build core components for a content understanding platform, such as entity extraction, topic modeling, creative summarization, and taxonomy generation
• Own experimentation, offline evaluation, and online validation of signal pipelines at massive scale
• Collaborate across engineering, infra, and product teams to productionize systems while meeting high standards for reliability and privacy

• 4+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding
• Deep understanding of information retrieval, semantic search, and query-document matching
• Strong hands-on experience with LLM fine-tuning, knowledge graph construction, and entity-centric modeling
• Experience working with multimodal models, including text, vision, metadata, or audio-based representations
• Proficiency in Python, and experience with one or more of ML frameworks like PyTorch, TensorFlow
• Background in statistical modeling, optimization, and ML theory
• Exposure to ad tech domains such as auction modeling, targeting, attribution, or creative optimization is a plus
• Demonstrated ability to deliver high-impact ML solutions in production environments
• Bachelor's in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field.

• 7+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding
• MS or PhD in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field.

Base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Employees also have the opportunity to become a shareholder through participation in discretionary employee stock programs. Employees are eligible for discretionary restricted stock unit awards, and can purchase stock at a discount if voluntarily participating in the Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Benefits.

Note: Benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

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Accepts applications to this posting on an ongoing basis.