Senior Algorithm Engineer

At ThetaRay, our purpose is to make the world a safer place by protecting the integrity of the global financial system. We do this by putting AI at the core of both our technology and our way of working. Our AI-driven solutions help banks and fintech companies worldwide detect and stop serious financial crime, from human trafficking and terrorist financing to sophisticated money laundering, while advanced technology, automation, and AI-driven tools help our teams collaborate smarter, move faster, and continuously improve how we build, deliver, and innovate. About the role: We are looking for a Senior Algorithm Engineer to turn expertise, initiative, and bold thinking into real impact on the next generation of AI-driven financial crime detection. If you combine strong software engineering and algorithmic thinking with hands-on experience in large-scale data processing and machine learning, and if you are motivated by turning data-driven models into robust, production-ready systems that power mission-critical financial crime detection for global banks and fintechs, ThetaRay could be your next challenge. What you’ll work on: Designing and developing scalable data processing pipelines and backend systems Writing efficient, high-quality, and maintainable code in Python and PySpark Optimizing large-scale data workflows and distributed computing processes Implementing and integrating machine learning solutions into production systems Translating analytical and algorithmic models into scalable applications Improving the performance, reliability, and scalability of data and ML pipelines Collaborating with data scientists, analysts, engineers, and R&D teams to bring solutions into production Conducting code reviews and promoting software engineering best practices Requirements 3+ years of experience in software development, algorithm engineering, or data engineering Expert-level Python programming skills Strong experience with PySpark / Apache Spark Experience working with large-scale distributed data processing Ability to write high-performance, optimized, and production-grade code Solid understanding of machine learning algorithms and concepts Experience implementing ML models in production environments Familiarity with supervised and unsupervised learning, feature engineering, and model evaluation and validation Experience with libraries such as NumPy, scikit-learn, TensorFlow, or PyTorch Strong understanding of data pipelines, ETL processes, and distributed systems Experience working with large and complex datasets Strong debugging, optimization, and performance tuning skills Strong analytical and problem-solving skills High attention to detail, code quality, and maintainability Strong communication and collaboration skills, with the ability to work independently and take ownership of technical solutions Advantages Familiarity with cloud environments or big data platforms