Job Description

ThetaRay provides AI-driven anti-financial crime technology used by global banks and fintechs to detect money laundering and financial crimes.

Our Israel office is a key R&D hub where engineering, data, and research teams work together to build scalable, production-ready systems that power ThetaRay’s platform.

We are looking for an Algorithm Researcher to join our team in Israel and help build the next generation of AI-driven financial crime detection.

In this role, you will work at the intersection of research, mathematics, and advanced AI, turning complex theoretical concepts into scalable, production-ready algorithms. You will solve high-dimensional real-world problems and contribute directly to mission-critical systems used by leading financial institutions worldwide.

Technology: Python, NumPy, SciPy, Pandas, PyTorch / TensorFlow, LLMs, RAG, vector databases, large-scale data processing

What you’ll work on:

• Designing and developing advanced algorithms for complex financial crime detection challenges
• Translating mathematical models and research concepts into scalable production systems
• Building and optimizing ML and LLM-based solutions for real-world deployment
• Working with transformers, attention mechanisms, sequence modeling, and representation learning
• Developing solutions using RAG, embedding models, vector databases, and generative AI evaluation frameworks
• Designing AI agents, tool-using LLM architectures, and autonomous decision-making pipelines
• Improving model accuracy, robustness, explainability, and inference efficiency
• Collaborating with engineers, data scientists, and domain experts to bring research into production

Requirements

• MSc or PhD in Physics, Applied Mathematics, Computational Mathematics, Statistics, or a related quantitative field
• 3+ years of experience in algorithm development, quantitative research, or advanced AI roles
• Strong background in linear algebra, probability theory, stochastic processes, optimization, numerical methods, and statistical modeling
• Proven experience turning mathematical concepts into robust algorithms
• Deep understanding of modern deep learning architectures, including transformers, attention mechanisms, sequence modeling, and representation learning
• Hands-on experience with PyTorch or TensorFlow
• Experience building, fine-tuning, optimizing, or deploying LLMs
• Familiarity with RAG, embedding models, vector databases, prompt engineering, and evaluation frameworks for generative AI
• Expert-level Python skills, including NumPy, SciPy, and Pandas
• Strong understanding of algorithm design, complexity analysis, data structures, and large-scale data processing
• Experience building AI-based systems in production
• Strong communication skills and the ability to explain complex concepts to both technical and business stakeholders

Advantages

• Background in signal processing, dynamical systems, or computational physics
• Experience with graph algorithms, anomaly detection, risk modeling, or information retrieval
• Experience with model optimization, quantization, or distillation
• Proven publication record