Senior Algorithm Engineer

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 a Senior Algorithm Engineer 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 software engineering, algorithms, and large-scale data processing, building scalable production systems that power mission-critical financial crime detection solutions. You will design efficient architectures, develop high-quality code, and turn data-driven and machine learning models into robust real-world applications.

Technology: Python, PySpark, Apache Spark, NumPy, scikit-learn, TensorFlow / PyTorch, ETL pipelines, distributed systems, large-scale data processing

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