Algorithm Researcher

Israel, Hod HaSharon
Full-time
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