ML Ops Engineer
Zeta Global3 months ago
Berlin, GermanyMid Level / Senior
Responsibilities
- Explore data, develop models, run rigorous experiments, and bring effective approaches into production.
- Work with structured and unstructured data, including feature engineering, dataset construction, labeling quality, leakage checks, and evaluation discipline.
- Compare modeling approaches using metrics, error analysis, and practical tradeoffs.
- Build LLM and GenAI workflows where relevant, including fine-tuning, retrieval-augmented generation, evaluation, and prompt/versioning.
- Package models, build inference paths, monitor performance, and iterate after launch.
- Own work from problem framing through experimentation, implementation, and rollout.
- Collaborate with engineers, product partners, and data scientists on meaningful internal product projects.
- Contribute to ML patent submissions and participate in weekly ML and research paper review meetings.
- Support multiple experience levels, including potential modeling leadership and mentorship for senior candidates.
Requirements
- At least 3 years of software or applied machine learning experience.
- Strong foundation in machine learning, statistics, and experiment design.
- Experience building models for real business or product problems.
- Experience with feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
- Ability to evaluate approaches using metrics, error analysis, and tradeoff analysis across accuracy, latency, cost, and maintainability.
- Proficiency in Python and ability to write clean, modular, testable code.
- Experience developing and deploying machine learning solutions in a cloud environment, especially AWS.
- Master’s degree in science or engineering, or equivalent practical experience.
- Preferred experience with scikit-learn, PyTorch, TensorFlow, XGBoost, MLflow, W&B, SQL, data warehouses or lakes, Airflow, dbt, Spark, feature stores, embedding pipelines, vector search, HTTP or gRPC APIs, Docker, orchestration, and GitLab CI.
- Excellent written and spoken English and ability to communicate technical methods, results, and limitations to technical and non-technical audiences.
Benefits
- Flexible hours and remote/home office options.
- Calm engineers-only office when working on-site.
- Collaboration on ML patent submissions and weekly ML/research paper review meetings.
- High trust, autonomy, short approval cycles, and protected focus time.
- Competitive compensation including stock options.
Tech Stack
Categories
About Zeta Global
Zeta Global builds an AI-powered marketing cloud that unifies customer data, analytics, and omnichannel activation for enterprise brands and agencies. Its Zeta Marketing Platform combines martech and adtech—spanning CRM, email, display, and social—to acquire, grow, and retain customers on a subscription and media-buying model. Founded in 2007 and headquartered in New York City, Zeta is a public company trading on the NYSE under the ticker ZETA.