דרושים » הנדסה » מהנדס /ת AI עבור ארגון גדול באיזור הצפון

we are seeking a Lead AI Engineer! We are seeking a Lead AI Engineer to spearhead the design and implementation of large-scale enterprise AI solutions. This is a hybrid-role (50/50 architecture and hands-on development) with a core focus on RAG (Retrieval-Augmented Generation) systems and AI Agents in a hybrid environment (Azure + On-Prem). As a key member of the team, you will drive technological innovation and integrate advanced AI capabilities into the organizational workflow. Responsibilities
* Advise business units and lead AI use-case discovery and execution.
* Design AI solution architectures based on LLMs, RAG, and AI Agents
* Perform hands-on end-to-end development of AI services.
* Build RAG pipelines, including ingestion, chunking, embeddings, and retrieval strategies.
* Integrate AI solutions with enterprise systems ( SharePoint, APIs, and internal platforms
* Develop reusable components for the core AI platform.
* Work extensively with Microsoft 365, Graph API, and Teams
* Implement robust security mechanisms, permissions, and data Loss Prevention (DLP).
* Mentor teams and establish AI development Best Practices Full-Time | Haifa

As a Research Scientist in Model Evaluation, you are the ultimate authority on model quality and utility. You will design the automated judges, reward models, evaluation datasets, and benchmarking ecosystems that determine the future of LTX. Your mission is to provide the "ground truth" for our pre-training and post-training teams. You will blend the rigor of a researcher with the intuition of a product-thinker, developing metrics that capture both the aesthetic soul of a video and the functional precision required for high-stakes professional use.

Key Responsibilities
Steer Training & Research: Systematically evaluate model checkpoints to provide actionable insights that guide training experiments and architectural decisions.
Design Benchmark Ecosystems: Develop and run rigorous benchmarks for release candidates against competitive models, ensuring LTX-2 remains world-class.
Build Next-Gen Metrics: Develop robust automatic metrics and Reward Models (e.g., for RL, ITS, auto-research agents) that quantify complex attributes like temporal coherence, physical correctness, spatial accuracy, and foley synchronization.
Diagnose & Analyze: Perform deep root-cause analysis on model failures, providing the diagnostic clarity needed for researchers to implement targeted fixes.
Scale Evaluation: Collaborate with platform engineers to deploy evaluation frameworks across large-scale GPU clusters.