ML Ops Engineer
Zeta Global3 months ago
Prague, CzechiaMid Level / Senior
Responsibilities
- Explore data, construct datasets, engineer features, assess labeling quality, check for leakage, and maintain disciplined train/validation/test processes.
- Develop, compare, and improve machine learning models using clear metrics, error analysis, and tradeoff analysis across accuracy, latency, cost, and maintainability.
- Run rigorous experiments involving classical machine learning, deep learning, and relevant LLM or GenAI workflows.
- Package models, build inference paths, deploy solutions to the cloud, monitor performance, and iterate after launch.
- Own projects end-to-end from problem framing through experimentation, implementation, and rollout.
- Collaborate with engineers, product partners, and data scientists on meaningful internal product projects.
- Explain technical methods, results, and limitations to both technical and non-technical audiences.
- Participate in ML patent submissions and weekly ML or research paper review meetings.
Requirements
- At least 3 years of software or applied machine learning experience.
- Strong foundations in machine learning, statistics, and experiment design.
- Experience building models for real business or product problems and working with structured and unstructured data.
- Proficiency in Python and ability to write clean, modular, testable code.
- Experience deploying machine learning solutions in a cloud environment, especially AWS.
- Ability to take work from problem framing and experimentation through implementation, rollout, monitoring, and iteration.
- Master’s degree in science or engineering, such as computer science, mathematics, physics, or statistics, or equivalent practical experience.
- Strong written and spoken English and ability to communicate methods, results, and limitations to technical and non-technical audiences.
- 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/gRPC inference services, Docker, orchestration, and GitLab CI.
- Preferred publications, patents, Kaggle or competition results, or open-source machine learning contributions.
Benefits
- Flexible hours and remote/home office options.
- Calm engineers-only office when working on-site.
- High-trust, autonomous, multicultural engineering team with peer support.
- Opportunities to collaborate on ML patent submissions and attend weekly ML/research paper review meetings.
- Healthy meeting policy, protected focus time, short approval cycles, and strong product partnership.
- 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.