WHO WE ARE
Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
Key Responsibilities• Technical strategy and architecture. Define the AI/ML architecture and technical roadmap across the portfolio. Identify shared capabilities, establish clear interfaces, and guide build-versus-buy decisions while respecting product-specific requirements.
• Predictive ML and optimization. Lead advances in prediction, targeting, ranking, bidding, pacing, and personalization. Guide feature development, training, calibration, and serving, addressing sparse signals, delayed outcomes, and changing data distributions.
• Agentic frameworks and agents. Design reusable orchestration, tool integration, retrieval, state and memory, and multi-agent coordination. Build workflows for campaign planning, insights, recommendations, and execution, with explicit permissions, human approval where needed, and recoverable failure handling.
• Portfolio integration. Partner with Predict, Agentic Frameworks, Email DSP/SSP, and agentic teams to connect models, data, and services through well-defined APIs and shared evaluation practices. Turn successful patterns into reusable components and practical migration paths.
• Production engineering. Own critical designs and implementations across data pipelines, training, deployment, and inference. Establish MLOps and LLMOps practices for reproducibility, versioning, automated testing, observability, and safe rollouts and rollbacks.
• Evaluation and business impact. Define offline benchmarks and online experiments tied to advertiser outcomes. Evaluate prediction quality, calibration, agent task completion, tool accuracy, latency, and cost; use A/B testing and incrementality methods where appropriate.
• Reliability and responsible AI. Set standards for service performance, drift detection, data quality, and incident response. Build privacy-aware data access, auditability, and protection against prompt injection, data leakage, and unintended agent actions.
• Technical leadership. Partner with engineering, data science, product, and business leaders to turn ambiguous needs into deliverable plans. Lead design and code reviews, mentor senior engineers, and resolve technical decisions across teams.
Required Qualifications• 12+ years of relevant software engineering and applied ML experience, or equivalent demonstrated expertise, including substantial ownership of production ML systems and technical leadership across multiple teams.
• Deep expertise in predictive ML for ranking, recommendation, classification, or optimization, with strong foundations in statistics, experimentation, model evaluation, and the full model lifecycle.
• Hands-on experience delivering LLM applications and agentic workflows to production, including tool use, retrieval, orchestration, evaluation, guardrails, and operational monitoring.
• Proven ability to architect distributed, high-throughput, low-latency systems and make sound trade-offs across model quality, infrastructure cost, and operational complexity.
• Strong Python skills and proficiency in Java, Go, or a comparable backend language; experience with PyTorch or TensorFlow, SQL, and large-scale data or streaming systems such as Spark and Kafka.
• Experience with cloud infrastructure, preferably AWS, containerization, CI/CD, model serving, and production observability; familiarity with relational, NoSQL, caching, and retrieval systems.
• Ability to influence without direct authority, communicate architectural decisions clearly, mentor experienced engineers, and translate business objectives into measurable technical outcomes.
Preferred Qualifications• AdTech experience across DSPs, SSPs, real-time bidding, audience modeling, identity, attribution, or measurement; relevant experience in recommendation systems or marketplaces is also valued.
• Experience with causal inference, uplift modeling, contextual bandits, constrained optimization, or online learning in production.
• Experience with privacy-aware identity and audience systems, email advertising, or integrating ML capabilities across multiple products.
• Experience optimizing model and LLM inference, selecting and adapting models, or building reusable ML and agent platforms adopted by multiple teams.
PEOPLE & CULTURE AT ZETA
Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.
We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/
ZETA IN THE NEWS!
https://zetaglobal.com/press/?cat=press-releases
Skills Required
- 12+ years of relevant software engineering and applied machine learning experience, or equivalent demonstrated expertise
- Substantial ownership of production machine learning systems and technical leadership across multiple teams
- Deep expertise in predictive machine learning for ranking, recommendation, classification, or optimization
- Strong foundations in statistics, experimentation, model evaluation, and the full model lifecycle
- Hands-on experience delivering production LLM applications and agentic workflows, including tool use, retrieval, orchestration, evaluation, guardrails, and monitoring
- Experience architecting distributed, high-throughput, low-latency systems
- Strong Python skills and proficiency in Java, Go, or a comparable backend language
- Experience with PyTorch or TensorFlow, SQL, and large-scale data or streaming systems such as Spark and Kafka
- Experience with cloud infrastructure, preferably AWS, containerization, CI/CD, model serving, and production observability
- Familiarity with relational, NoSQL, caching, and retrieval systems
- Ability to influence without direct authority, communicate architectural decisions, mentor experienced engineers, and translate business objectives into measurable technical outcomes
- AdTech experience across DSPs, SSPs, real-time bidding, audience modeling, identity, attribution, or measurement
- Experience with recommendation systems or marketplaces
- Experience with causal inference, uplift modeling, contextual bandits, constrained optimization, or online learning in production
- Experience with privacy-aware identity and audience systems, email advertising, or integrating machine learning capabilities across multiple products
- Experience optimizing model and LLM inference, selecting and adapting models, or building reusable ML and agent platforms
What the Team is Saying
Zeta Global Compensation & Benefits Highlights
How does Zeta Global ensure its pay and bonus plans are competitive?
Zeta Global supports competitive compensation through a mix of base pay, equity, performance incentives, financial benefits and employee feedback-informed rewards. The company’s total rewards approach connects compensation with ownership, financial planning and benefits that support employees’ broader well-being.
- Competitive pay and incentives: Zeta lists competitive pay, equity, performance bonuses and an employee stock purchase plan as part of its compensation and total rewards offerings. Employees also describe compensation as a strength. A software engineer said Zeta offers “good compensation,” “best appraisals and pay raise” and a “supportive work environment,” while a director cited “compensation” as one of the strengths of the company.
- Equity and ownership: Zeta offers company equity and an employee stock purchase plan, giving employees ways to participate in the company’s growth. Its broader financial benefits also include a 401(k) with company match, monthly financial workshops, commuter benefits and insurance coverage, reinforcing compensation as part of a larger financial wellness package.
- Performance-oriented rewards: Employee reviews describe Zeta’s compensation as tied to performance and growth. One employee said, “Zeta pays well,” while another said compensation is “within industry range and revised every year.” A finance analyst cited “great incentives,” and a director described Zeta as a place to “shape your career” with room to move up. (Comparably; Glassdoor reviews; Indeed reviews)
- Benefits that strengthen total rewards: Zeta’s rewards package extends beyond pay through health, dental and vision insurance, mental health benefits, pet insurance, flexible time off, parental leave, adoption assistance, fertility and family-building support, travel assistance for reproductive health procedures, volunteer days and wellness resources. The company also says it uses wellness surveys and employee feedback to shape benefits updates, including expanded parental leave and adoption assistance.
- External signals:
- Compensation sentiment: Employees on external review sites describe Zeta’s compensation as “good,” “great” and competitive, with reviews citing pay raises, incentives, benefits and performance-based earning potential. (Glassdoor reviews; Indeed reviews; Comparably)
- Benefits signals: External profile data lists company equity, performance bonuses, an employee stock purchase plan and a home-office stipend for remote employees.
- Financial wellness: Zeta’s benefits include 401(k) matching, financial workshops, insurance coverage and employee stock purchase participation.
Bottom line: Zeta Global’s compensation approach combines competitive pay, performance incentives, equity, stock purchase access and broad benefits, giving employees both near-term rewards and longer-term financial participation in the company’s growth.
Zeta Global Insights
What We Do
Zeta Global (NYSE: ZETA) is the AI Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world.
Why Work With Us
At Zeta, people have the freedom to think creatively, take initiative, and grow. We value curiosity, innovation, and teamwork, empowering everyone to use AI and technology in smarter ways to drive impact for clients, consumers, and each other while shaping the future together.
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Zeta Global Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
