AdTechTalent
Data Science1 month agoRemote

Zeta Global

ML Ops Engineer

machine learningdata sciencepythonAWSdeep learningLLMGenAIcloudMLflowPyTorchTensorFlowXGBoostSQLAirflowdbtSparkDockerCI/CDGitLab CIHTTP APIgRPCexperiment designfeature engineeringmodel deployment

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Mid-level

Years experience

3-5

Location

Berlin, Germany

Full job description

Zeta Global is seeking a mid-level ML Engineer / Data Scientist with 3+ years of software or applied ML experience to design, build, and improve machine learning solutions primarily on AWS. The role involves data exploration, model development, experimentation, and production deployment with a focus on clean, modular Python code. Candidates should have a strong foundation in machine learning, statistics, experiment design, and experience with structured and unstructured data. Responsibilities include owning projects end-to-end from problem framing to rollout, collaborating with engineers and product teams, and working in a multicultural environment. A Master's degree in a relevant field or equivalent experience is required. Preferred skills include experience with scikit-learn, PyTorch, TensorFlow, XGBoost, ML experiment tracking tools, SQL, data pipeline tools, Docker, and CI/CD. The position offers flexible hours, hybrid remote options, competitive compensation including stock options, and a supportive engineering-focused team in Berlin, Germany.

What you'll do

  • Design, build, and improve machine learning solutions in a dynamic cloud environment
  • Explore data, develop models, run rigorous experiments
  • Bring best approaches into production with reliable, reproducible workflow
  • Work collaboratively in multicultural teams
  • Own work from problem framing through experimentation, implementation, and rollout

Requirements

  • Strong foundation in machine learning, statistics and experiment design
  • Experience building models for real business or product problems
  • Comfortable working with structured and unstructured data
  • Able to compare approaches with clear metrics, error analysis, and sound judgment about tradeoffs
  • Interest in modern ML including classical ML, deep learning, and LLM / GenAI workflows
  • 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 to 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 or equivalent practical experience

Tech stack

PythonAWSscikit-learnPyTorchTensorFlowXGBoostMLflowWeights & BiasesSQLAirflowdbtSparkDockerGitLab CIHTTP APIsgRPC

Benefits

Hands-on modeling work with room to explore, benchmark, and improve real systemsCollaboration on ML patent submissions and participation in weekly ML / research paper review meetingsMulticultural, engineering-focused team with strong peer supportHigh trust and autonomy with clear goals and freedom in how to reach themInternal product impact with meaningful projectsShort approval cycles and solid product partnershipHealthy meeting policy and emphasis on protecting focus timeFlexible hours, remote/home office options, and a calm, engineers-only office when on-siteCompetitive compensation including stock options

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