Machine Learning Engineer

An elite, tier-1 global financial powerhouse recognized as one of the largest and most prestigious hedge funds in the world.

Managing multi-billion dollar funds with a massive global workforce, the company operates at the absolute frontier of technology, engineering highly sophisticated algorithmic trading infrastructures, real-time risk assessment matrices, and live market-pricing engines.

The company maintains a highly selective, rapidly growing engineering hub in Central Israel (exceptionally accessible via the train network) that mirrors the high-intensity, competitive compensation structures and elite technical standards of its New York headquarters.

Position Overview-

• Lead AI/ML Infrastructure Engineer serving as the exclusive, standalone technical function in Israel within an elite, global ML Engineering and Data Science group, reporting directly to a Group Lead based in New York.

• Balancing a high-impact split between 60% Advanced AI, NLP, and LLM Research and 40% Production-Grade AI/ML Infrastructure Engineering.

• Architecture, training, and deploying advanced models using frameworks like PyTorch and TensorFlow, alongside designing enterprise-grade Retrieval-Augmented Generation (RAG) frameworks.

• Engineering robust MLOps pipelines from scratch, leveraging Python, CI/CD, Terraform, and Kubernetes to ensure hyper-scalable, low-latency model deployments across hybrid Cloud (AWS/GCP) and On-Premise environments.

• Establishing end-to-end observability, automated build/release pipelines, and high-throughput data processing workflows to support mission-critical, live algorithmic trading clusters.

Requirements-

• Academic Background: M.Sc. or Ph.D. in Exact Sciences (Computer Science, Mathematics, Physics, or Data Science) strictly from a Top-Tier Research University – Mandatory

• 3+ years of proven professional experience operating as an AI Engineer, ML Engineer, or Data Scientist within high-caliber production environments – Mandatory

• Expert-level, production-grade programming proficiency in Python – Mandatory

• Extensive, hands-on experience architectural deployment over containerized environments (Kubernetes) and orchestration pipelines – Mandatory

• Strong technical command of modern cloud infrastructure (AWS or GCP) – Significant Advantage

• Proven experience building enterprise RAG systems, LLM fine-tuning pipelines, or advanced NLP architectures – Significant Advantage