Machine Learning Engineer

Hello Heart
Tel Aviv
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: bachelorsSkills: ["Collaboration","Communication","Debugging","Rigor","Translation of insights"]

Own end-to-end development and production deployment of predictive machine learning models that power user engagement, cardiovascular risk stratification, and personalized health recommendations. Apply strong statistics—probability, inference, Bayesian methods, causal inference, and experimental design—to build reliable models. Write production-grade Python with testing, observability, and real-time serving, partnering cross-functionally to deliver scalable, monitored healthcare AI systems.

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Hello Heart
Hello Heart
1 month ago

Machine Learning Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Own end-to-end development and production deployment of predictive machine learning models that power user engagement, cardiovascular risk stratification, and personalized health recommendations. Apply strong statistics—probability, inference, Bayesian methods, causal inference, and experimental design—to build reliable models. Write production-grade Python with testing, observability, and real-time serving, partnering cross-functionally to deliver scalable, monitored healthcare AI systems.
Location: Tel Aviv
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Lead end-to-end development and production ownership of predictive ML models from exploration and feature engineering through training, validation, deployment, real-time serving, and monitoring.
  • •Apply statistical foundations to model design, feature selection, uncertainty quantification, and result interpretation.
  • •Write and maintain production-grade, well-tested Python code, owning observability, debugging, reliability, and scalability.
  • •Use AI coding assistants to accelerate development workflows including code review, testing, debugging, and documentation.
  • •Research and implement advanced ML methods (supervised/unsupervised learning, causal inference, deep learning, reinforcement learning) and evaluate impact using A/B tests.

Key Requirements

  • •5+ years building, deploying, operating, and debugging ML systems in production with end-to-end ownership from modeling through deployment.
  • •Bachelor’s degree in Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field.
  • •Deep expertise in statistics and probability, including inference, hypothesis testing, Bayesian methods, causal inference, and experimental design for healthcare use cases.
  • •Strong Python software engineering skills for production-grade, maintainable, well-tested code.
  • •Experience with ML frameworks and production pipelines, including CI/CD, real-time or low-latency model serving, monitoring, and observability.
Experience:5+ yearsHealthcareAIMachine learningProduction systems
Education:Bachelor's in Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field
Skills:CollaborationCommunicationDebuggingRigorTranslation of insights
Languages:English
Tech Stack:PythonPyTorchScikit-learnXGBoostLightGBMCI/CDA/B testingReinforcement learningCausal inferenceDeep learning

Company Brief

Hello Heart
Provides a digital cardiovascular health platform that helps users manage blood pressure, heart health, and related risks via mobile apps, connected devices, personalized insights, and employer or health plan-based programs to improve outcomes and engagement.
Industry: HealthTech
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