Requirements
- Strong foundation in machine learning, statistics and experiment design.
- Experience building models for real business or product problems, not only academic benchmarks.
- Comfortable working with structured and unstructured data: feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
- Able to compare approaches with clear metrics, error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
- Interest in modern ML, including classical ML, deep learning, and LLM / GenAI workflows where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
- Proficient in Python and able to write clean, modular, testable code.
- Experience developing and deploying ML solutions in a cloud environment, especially AWS.
- Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.
- Independent engineer who can own work from problem framing → experimentation → implementation → rollout.
- Excellent written and spoken English.
- Enjoy working closely with engineers, product partners, and other data scientists.
- Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.
- Master’s degree in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar), or equivalent practical experience.
Nice to Have
- Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar modeling stacks.
- Familiarity with ML experiment tracking and reproducibility (e.g. MLflow, W&B).
- Experience with SQL, data warehouses/lakes, and pipeline tools such as Airflow, dbt, or Spark.
- Exposure to feature stores, embedding pipelines, or vector search for retrieval-based systems.
- Experience building HTTP/gRPC APIs or lightweight services around model inference.
- Working knowledge of Docker, basic orchestration, and CI/CD (e.g. GitLab CI).
- Experience in agile, remote and async team environments.
- Publications, patents, Kag游戏副本 results, or open-source ML contributions.
Benefits
- Hands-on modeling work with room to explore, benchmark, and improve real systems.
- Collaboration on ML patent submissions and participation in weekly ML / research paper review meetings.
- A multicultural, engineering-focused team with strong peer support.
- High trust and autonomy—clear goals, freedom in how to reach them.
- Internal product impact: meaningful projects that improve developer and user experience, not endless maintenance tickets.
- Short approval cycles and solid product partnership.
- A healthy meeting policy and emphasis on protecting focus time.
- Flexible hours, remote/home office options, and a calm, engineers-only office when on-site.
- Competitive compensation, including stock options.
Work Arrangement
Hybrid — New York City
What you might like about this role
Hands-on modeling work with room to explore, benchmark, and improve real systems. Collaboration on ML patent submissions and participation in weekly ML / research paper review meetings. A multicultural, engineering-focused team with strong peer support. High trust and autonomy—clear goals, freedom in how to reach them. Internal product impact: meaningful projects that improve developer and user experience, not endless maintenance tickets. Short approval cycles and solid product partnership. A healthy meeting policy and emphasis on protecting focus time. Flexible hours, remote/home office options, and a calm, engineers-only office when on-site. Competitive compensation, including stock options.
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/
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