Zeta Global
We deliver better experiences for consumers and better results for your brand.
Principal AI/ML Engineer – AdTech
Machine Learning EngineerMachine Learning EngineerFull TimeRemoteTeam 1,001-5,000Since 2007H1B SponsorCompany SiteLinkedIn
Location
United States
Posted
138 days ago
Salary
$300K - $400K / year
10 yrs expEnglishApacheAWSCassandraCloudDistributed SystemsDockerDynamo DBHadoopJavaKafkaKubernetesMy SQLNo SQLPostgresPythonPy TorchRedisSparkSQLTensorflowGo
Job Description
• Lead the design and implementation of scalable, high-performance, and resilient ML solutions for AdTech use cases.
• 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.
• 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.
• Develop intelligent systems using AI agents and agentic workflows to automate and optimize end-to-end campaign processes.
• Partner with engineering, product, and data science teams to translate marketing objectives into ML-driven solutions.
• Ensure system robustness and stability for ML services in a high-concurrency, low-latency environment.
• Provide technical guidance and mentorship to other engineers and data scientists, fostering a culture of excellence in engineering and ML best practices.
Job Requirements
- 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).
- 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).
- Familiarity with containerization and orchestration technologies (Docker, Kubernetes) for deploying and managing services at scale.
- Excellent communication, presentation, and interpersonal skills, with ability to convey complex ML concepts to technical and non-technical stakeholders.
Benefits
- Unlimited PTO
- Excellent medical, dental, and vision coverage
- Employee Equity
- Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!
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