Senior Machine Learning Engineer

1 week ago

Tel Aviv, Tel Aviv, Israel StarHunter Full time ₪120,000 - ₪180,000 per year

We are looking for an Algorithm Engineer with strong expertise in machine learning, data-driven optimization, and AI system design to build and scale intelligent features for a high-usage consumer product. The ideal candidate has experience turning complex datasets into production-ready models that directly impact user behavior, product KPIs, and business outcomes.

Key Responsibilities

  • Research, design, and implement advanced ML and AI algorithms that improve forecasting, personalization, fraud detection, risk modeling, or customer experience.
  • Analyze large-scale datasets to extract insights, detect patterns, and solve optimization problems.
  • Build end-to-end data-driven systems, including model training, evaluation, deployment, and ongoing performance tuning.
  • Design and implement models for user prediction, ranking, segmentation, scoring mechanisms, or real-time decision engines.
  • Own model lifecycle in production: monitoring, versioning, retraining, and A/B experimentation.
  • Work closely with Product, Data, and Engineering teams to translate business problems into algorithmic solutions.
  • Design scalable backend services supporting real-time and long-term data needs (e.g., Redis, SQL, Redshift).
  • Communicate research conclusions and model impact to technical and non-technical stakeholders.

Required Skills & Experience

  • 4–5+ years of hands-on industry experience in algorithm development / ML / applied data science
  • Strong programming skills:
    Python, Java
  • Experience with machine learning methods such as DNN, tree-based models, reinforcement learning, etc.
  • Strong background in statistics, optimization, and data modeling
  • Experience working with large-scale B2C data or high-velocity transactional systems
  • Practical experience deploying ML models into production environments

Nice to Have

  • Experience in fintech, fraud prevention, credit scoring, payments, or risk analytics
  • Experience building personalization systems (recommendation, ranking, behavioral modeling)
  • Experience with backend development
  • Knowledge of MLOps, model monitoring, real-time inference systems

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