עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
20,000-35,000 ₪
What You'll Do
- Design and ship the ML backbone of Gini AI Workers - routing, tool selection, reasoning, memory, evaluation.
- Build evaluation and feedback loops - offline evals, online A/B, regression harnesses, human-in-the-loop labeling pipelines.
- Optimize cost and latency across the agent stack: prompt engineering, model routing (frontier ↔ small ↔ fine-tuned), caching, speculative decoding, distillation.
- Fine-tune and/or RAG-tune models for vertical enterprise tasks (invoice extraction, PO matching, ticket triage, forecasting).
- Own the ML infra - training pipelines, experiment tracking, model registry, deployment, monitoring, drift detection.
- Partner with backend + product to turn research into shipped features on a weekly cadence.
- Design and ship the ML backbone of Gini AI Workers - routing, tool selection, reasoning, memory, evaluation.
- Build evaluation and feedback loops - offline evals, online A/B, regression harnesses, human-in-the-loop labeling pipelines.
- Optimize cost and latency across the agent stack: prompt engineering, model routing (frontier ↔ small ↔ fine-tuned), caching, speculative decoding, distillation.
- Fine-tune and/or RAG-tune models for vertical enterprise tasks (invoice extraction, PO matching, ticket triage, forecasting).
- Own the ML infra - training pipelines, experiment tracking, model registry, deployment, monitoring, drift detection.
- Partner with backend + product to turn research into shipped features on a weekly cadence.
Requirements:
- 4+ years of ML engineering in production (not just research or notebooks).
- Hands-on LLM experience in 2025-2026: agentic systems, tool-use, function-calling, RAG, structured output, eval design.
- Strong Python. Comfortable with PyTorch/JAX and one serving stack (vLLM, TGI, TensorRT-LLM, SageMaker, or similar).
- You've built an eval pipeline that actually caught a regression in prod.
- You read the papers and know which ones to ignore.
Nice to Have
- Experience with MCP, LangGraph, DSPy, or custom agent frameworks.
- Fine-tuning (LoRA/QLoRA, DPO/ORPO, RLAIF) on open-weight models (Llama, Qwen, Mistral, DeepSeek).
- Vector DBs (pgvector, Pinecone, Weaviate, Qdrant), reranking, hybrid retrieval.
- Prior work on multi-agent systems or enterprise copilots.
- 4+ years of ML engineering in production (not just research or notebooks).
- Hands-on LLM experience in 2025-2026: agentic systems, tool-use, function-calling, RAG, structured output, eval design.
- Strong Python. Comfortable with PyTorch/JAX and one serving stack (vLLM, TGI, TensorRT-LLM, SageMaker, or similar).
- You've built an eval pipeline that actually caught a regression in prod.
- You read the papers and know which ones to ignore.
Nice to Have
- Experience with MCP, LangGraph, DSPy, or custom agent frameworks.
- Fine-tuning (LoRA/QLoRA, DPO/ORPO, RLAIF) on open-weight models (Llama, Qwen, Mistral, DeepSeek).
- Vector DBs (pgvector, Pinecone, Weaviate, Qdrant), reranking, hybrid retrieval.
- Prior work on multi-agent systems or enterprise copilots.
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
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