Zeta Global is looking to develop advanced machine learning models and AI-driven features for their advertising platform to optimize campaigns, personalize user experiences, and generate creative content at a large scale and low latency.
Requirements
- Proven experience designing and building high-throughput, low-latency distributed systems or data pipelines for large-scale applications.
- Deep expertise in the programmatic advertising ecosystem, including Demand-Side Platforms (DSPs), real-time bidding (RTB), Supply-Side Platforms (SSPs), and ad exchanges.
- Proficiency in programming languages such as Java, Go, and Python for building both data-intensive backend services and ML tools.
- Hands-on experience with machine learning frameworks and libraries, especially PyTorch or TensorFlow, for developing and training models.
- Strong experience with big data and streaming frameworks (e.g., Apache Spark, Kafka, Hadoop) for processing and analyzing large datasets.
- Expertise with cloud platforms (preferably AWS) and related services for scalable ML model deployment and data storage.
- Experience with various data stores, including both SQL and NoSQL databases (e.g., MySQL/PostgreSQL, Cassandra, DynamoDB, Redis).
Responsibilities
- Lead the design and implementation of scalable, high-performance, and resilient ML solutions for AdTech use cases. You will set technical direction for integrating AI/ML into our Demand-Side Platform and broader ad tech stack.
- Architect and evolve the end-to-end machine learning pipeline – from data ingestion and training to real-time inference, for our real-time bidding, targeting, and optimization algorithms. Ensure that models seamlessly integrate with our ad serving architecture and handle low-latency, high-throughput requirements.
- Define the technical roadmap and vision for AI/ML in our platform, evaluating new tools and techniques (including the latest in deep learning and LLMs) and making strategic build-vs-buy decisions. Continuously assess emerging technologies to keep our AdTech capabilities on the cutting edge.
- Develop intelligent systems using AI agents and agentic workflows to automate and optimize end-to-end campaign processes. Leverage LLMs and generative AI to enable autonomous campaign management tasks such as audience segmentation, dynamic bid adjustments, and creative asset generation.
- Partner with engineering, product, and data science teams to translate marketing objectives into ML-driven solutions. Work closely with stakeholders to deliver innovative features – including those powered by Large Language Models (LLMs), that enhance our advertising products.
- Ensure system robustness and stability for ML services in a high-concurrency, low-latency environment. Optimize algorithms and infrastructure for speed and scalability, and implement monitoring to maintain model performance and uptime in production.
- Provide technical guidance and mentorship to other engineers and data scientists, fostering a culture of excellence in engineering and ML best practices. Review code and models, share knowledge, and champion continuous improvement across teams.
Other
- 10+ years of experience in software engineering or data science, with at least 3-5 years in a principal engineer or lead ML role (preferably in the AdTech/MarTech industry).
- Excellent communication, presentation, and interpersonal skills, with ability to convey complex ML concepts to technical and non-technical stakeholders.
- Experience with Large Language Models (LLMs) and generative AI applied to advertising, for example, using AI to generate ad copy, optimize creative content, or personalize messaging.
- Experience designing and implementing agentic workflows that enable autonomous decision-making and real-time optimization in marketing campaigns.
- Familiarity with microservices architecture and event-driven design patterns in distributed systems.
