About the role: We are looking for an Algorithm Researcher to turn expertise, initiative, and bold thinking into real impact on the next generation of AI-driven financial crime detection.
If you combine strong mathematical and research capabilities with advanced AI expertise, and if you are motivated by turning complex theoretical concepts into scalable, production-ready algorithms that solve real-world financial crime challenges, ThetaRay could be your next challenge.
?Responsibilities:
* 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
* MSc or PhD in Physics, Applied Mathematics, Computational Mathematics, or Statistics.
* At least 3 years of experience in algorithm development, quantitative research, or advanced AI/ML roles.
* Strong background in linear algebra and probability theory.
* Strong background in stochastic processes and optimization.
* Strong background in numerical methods and statistical modeling.
* 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 large language models (LLMs).
* Familiarity with RAG (retrieval-augmented generation), embedding models, and vector databases.
* Familiarity with prompt engineering and evaluation frameworks for generative AI.
* Expert-level Python skills, including NumPy, SciPy, and Pandas.
* Strong understanding of algorithm design, complexity analysis, and data structures.
* Experience with large-scale data processing.
* Experience building AI-based systems in production. Advantages:
* Background in signal processing, dynamical systems, or computational physics (Advantage).
* Experience with graph algorithms, anomaly detection, risk modeling, or information retrieval (Advantage).
* Experience with model optimization, quantization, or distillation (Advantage).
* Proven publication record in a relevant field (Advantage).
