AI Engineer

A premier, world-leading quantitative hedge fund and private investment enterprise managing tens of billions of dollars in assets under management (AUM).

The firm operates at the cutting edge of quantitative finance, machine learning, and advanced computing, engineering sophisticated algorithmic platforms and AI-driven systems that power global investment strategies and research at massive scale.

Employing thousands of professionals globally, the company maintains an elite, high-caliber engineering and research hub of dozens of specialists in Israel, collaborating closely with US headquarters.

Located in the Central region (walking distance from the train station), operating on a full-time, on-site work model.

Role Description-

• Serving as an AI / Machine Learning Software Engineer, designing, developing, and deploying advanced AI, LLM, and Machine Learning systems into production environments supporting high-impact financial operations.
• Architecting and deploying Agentic AI workflows and LLM applications, implementing tool calling/tool use, multi-agent orchestration, structured outputs, advanced retrieval systems (RAG), and rigorous evaluation frameworks (Evals).
• Building and optimizing supervised machine learning models, leading end-to-end feature engineering, data validation, and pipeline development while actively mitigating data leakage, overfitting, and data/concept drift.
• Developing production-grade software infrastructure in Python, ensuring high performance, fault tolerance, and low-latency execution.
• Collaborating extensively and daily with US-based quantitative researchers, engineers, and executive stakeholders.

Requirements-

• B.Sc. in Computer Science, Software Engineering, Mathematics, Physics, or a closely related quantitative/technical discipline – Mandatory
• 3+ years of hands-on experience in Software Engineering, ML Engineering, or AI Development with systems deployed into Production – Mandatory
• Deep programming proficiency and strong software design skills in Python – Mandatory
• Substantial hands-on experience with Python and Agentic AI architectures (Multi-Agent Orchestration, Tool Use, Structured Outputs, Retrieval/RAG, and Automated Evals) – Mandatory
• In-depth understanding of Supervised Machine Learning: Model Training, Cross-Validation, Feature Engineering, and managing Data Leakage, Overfitting, and Data Drift – Mandatory
• Exceptional, fluent English communication skills (written and verbal) for continuous collaboration with US teams – Mandatory
• Background in Fintech, Quantitative Trading, High-Performance Distributed Systems, or Advanced Research environments – Advantage