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Software Engineer - Privacy-Enhancing Technologies

Hello Ateko — Canada · Posted ~7 hours ago

Senior

Skills

Python Privacy-Enhancing Technologies Data anonymization De-identification Differential privacy DevOps Version control Continuous integration Continuous deployment Large-scale data analysis Machine learning Data science NumPy SciPy Pandas Polars PySpark PyTorch scikit-learn Matplotlib Seaborn Git CI/CD

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Summary ✨ AI‑Generated

A software engineering position focused on privacy-enhancing technologies and data science in regulated environments. You will develop Python-based solutions, work with large datasets, apply privacy techniques such as anonymization and differential privacy, and implement DevOps practices for data applications.

Highlights

Advanced engineering opportunity combining privacy-enhancing technologies, artificial intelligence, data science, cybersecurity, and large-scale data. The role offers work on complex datasets in regulated environments and modern data-science DevOps practices.

Description

Qualifications & Experience Education and Certifications Master's or Ph.D. in fields related to privacy-enhancing technologies, artificial intelligence, machine learning, cybersecurity, cryptography, computer science, data science, mathematics, or statistics.Relevant Experience 5+ years of recent demonstrated Python development experience with libraries such as numpy, scipy, pandas, polars, pyspark, pytorch, scikit-learn, and matplotlib/seaborn.3+ years of recent demonstrated extensive experience in DevOps principles, practices, and methodologies including SOLID principles, software version control, continuous integration and deployment for data science applications.Demonstrated experience analyzing and working with large, complex datasets within public sector, financial services, or similarly regulated environments. Demonstrated experience developing and implementing Privacy-Enhancing Technologies (PETs), including data anonymization, de-identification, differential privacy, secure multiparty computation, federated learning, homomorphic encryption, or similar privacy-preserving techniques.Demonstrated knowledge of data structures, data models, and data relationships, including structured, semi-structured, unstructured, nested, graph, and network-based datasets.Demonstrated experience using cloud-based data and analytics platforms, including Microsoft Azure, Microsoft Fabric, Azure Data Lake, Azure Databricks, Jupyter Notebooks, and Docker.