Machine Learning Engineer

A pioneering Digital Health and SaaS enterprise that leverages advanced artificial intelligence and machine learning to accelerate personalized medical research.

Backed by substantial venture funding from premier life-science and technology investors, the organization scales with a high-caliber team of several dozen professionals.

Located in a central Tel Aviv tech hub (highly accessible, situated directly on the light rail transit network), operating under a flexible hybrid model providing 2 days of remote work per week.

Position Overview-

• AI / Machine Learning Engineer (Production & Systems Focus) joining a newly established, strategic algorithmic group to spearhead the translation of complex research models into high-scale production systems.
• Operating at the critical intersection of Data Science Research and Core Software Engineering, breaking down experimental algorithms into high-throughput, structured pipelines.
• Architecting seamless architectural handoffs and functional interfaces between DS squads, Product Engineering, Data Pipelines, and application-facing teams.
• Engineering robust evaluation loops, continuous guardrails, observability stacks, and automated feedback cycles tailored for enterprise-grade LLM capabilities and predictive models.
• Optimizing system behaviors across massive multi-modal healthcare datasets, managing heavy Time Series and Tabular data, while scaling infrastructures to support rising computer vision (imaging) pipelines.
• Core Domain & Ecosystem- Machine Learning Engineering, MLOps, AI Infrastructure, Production ML Systems, Large Language Models (LLMs), Eval Loops & Observability, Time Series Architecture, Tabular Data Engineering, Python, Cloud-Native Data Pipelines.

Requirements-

• Academic Background: B.Sc. or higher in a quantitative scientific discipline (Computer Science, Software Engineering, Data Science, Bio-Informatics, or a related field) – Mandatory
• 5+ years of proven professional experience operating as a Machine Learning Engineer, Data Scientist, or Algorithm Developer – Mandatory
• 2+ years of dedicated, hands-on experience deploying and maintaining AI/ML models within live, high-scale Production environments – Mandatory
• Deep, practical technical proficiency working with modern AI tools, Generative AI frameworks, or Large Language Models (LLMs) – Mandatory
• Strong system-level mindset with the architectural capacity to bridge the gap between heavy scientific theory and resilient, production-grade software engineering – Mandatory

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