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AI Developer

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Onsite

AI Developer

Hire-Match

AI Developer

Skills

PythonPyTorchTensorFlowData AnalysisMachine LearningAI

2 months ago

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Important information


Contract type:

Permanent

Location:

Ramat Gan, Israel

Work mode:

Onsite

Published on:

24 August 2026

What they need


HireMatch builds an AI-powered hiring platform that turns resumes, assessments, interviews, and candidate data into structured insights to help teams make faster, fairer, and more confident hiring decisions. We go beyond keyword matching with context-aware evaluation, predictive fit signals, and real-time dashboards that surface top candidates instantly. Our mission is to undo the hiring black box and bring transparency, merit, and measurable impact to recruiting — all powered by scalable AI and analytics.

Position Description

As an AI Developer, you will build and ship machine learning and generative AI features that power the product, working across the full lifecycle from prototyping to production deployment.

Responsibilities

  • Design, build, and deploy machine learning models or LLM-based features into production
  • Build and maintain RAG pipelines, prompt workflows, or fine-tuning processes for product features
  • Monitor deployed models for performance, drift, and cost, iterating as needed
  • Collaborate with product and engineering teams to translate requirements into AI-powered features
  • Evaluate and implement guardrails for generative outputs to ensure safety and reliability

Must-have

  • 2-5 years of hands-on experience with Python and a major ML framework (PyTorch or TensorFlow)
  • Experience building LLM/GenAI applications (RAG pipelines, vector databases, or agent frameworks such as LangChain)
  • Experience with MLOps practices, model deployment, monitoring, and versioning in production
  • Experience with a cloud ML platform (SageMaker, Vertex AI, or equivalent)
  • Applied background in statistics or applied mathematics relevant to ML model development

Nice to Have

  • Published research or meaningful open-source contributions
  • Large-scale model fine-tuning or training experience
  • A shipped, production AI feature, not limited to prototype or hackathon work
  • Experience with evaluation and guardrail design for generative outputs

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