Developer - Privacy Enhancing Technology

• Develop and implement privacy-enhancing technologies (PETs) for structured and unstructured datasets in collaboration with Subject Matter Experts (SMEs).
• Apply advanced core computing principles to efficiently integrate multiple open-source libraries, components and platforms into cohesive and operational solutions.
• Design, develop and validate proof of concept solutions with a focus on deployment in production environments.
• Develop and Implement test harnesses to evaluate and compare solution approaches against performance, scalability, quality and privacy metrics.
• Create, maintain and optimize Extract-Transform-Load (ETL) pipelines to ingest, transform, validate, sanitize and prepare data for processing and analysis.
• Provision, configure, orchestrate and manage cloud resources in support of deployed solution.
• Assess, evaluate, and recommend emerging tools, technologies, and processes to improve solution performance, efficiency, scalability and maintainability.
• Analyze results and technical findings, develop recommendations, and present conclusions to stakeholders to support the scalable deployment of operationally viable PET solutions.
• Prepare technical reports, data artifacts, presentations, documentation, and other project deliverables required to support project execution and decision-making.
• Other related activities or deliverables as required.

We are Systematix and we are currently seeking a Senior Developer - Privacy Enhancing Technology for an opportunity with a public sector client. The ideal candidate must hold an active Government of Canada Secret (Level II) security clearance. This is a hybrid role requiring up to 4 days on-site per month, with an expected start date in October 2026 and a 12-month duration., * Master’s or Ph.D. in fields related to privacy-enhancing technologies, artificial intelligence, machine learning, cybersecurity, cryptography, computer science, data science, mathematics, statistics.

• Minimum of 5 years of recent demonstrated Python development experience with the following libraries: numpy, scipy, pandas, polars, pyspark, pytorch, scikit-learn, matplotlib/seaborn.
• Minimum of 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.
• Experience analyzing and working with large, complex datasets within public sector, financial services, or similarly regulated environments.
• Experience developing and implementing Privacy-Enhancing Technologies (PETs), including data anonymization, de-identification, differential privacy, secure multi-party computation, federated learning, homomorphic encryption, or similar privacy-preserving techniques.
• Knowledge of data structures, data models, and data relationships, including structured, semi-structured, unstructured, nested, graph, and network-based datasets.
• Experience using cloud-based data and analytics platforms, including Microsoft Azure, Microsoft Fabric, Azure Data Lake, Azure Databricks, Jupyter Notebooks, Docker.
• Knowledge of Linux computing environments and basic scripting concepts.
• Knowledge of privacy-preserving and statistical techniques, such as Monte Carlo simulation, Markov models, synthetic data generation, differential privacy, homomorphic encryption, and zero-knowledge proofs.
• Knowledge of machine learning concepts and techniques, including GANs, transformers, auto-encoders, RAG, and machine learning model development methodologies.
• Knowledge of infrastructure management and automation concepts, including infrastructure as code (IaC), Ansible, Terraform, Puppet, Chef, or equivalent technologies.

Candidates must outline in detail how they meet the above requirements.

Pay Disclosure

The average hourly pay range for this field is as follows:

• Junior: 0-5 years of experience - $40-75/hr
• Intermediate: 6-9 years of experience - $60-100/hr
• Senior: 10+ years of experience - $90-150/hr

Compensation is commensurate with these standards; exceptions may apply based on experience, skills, and market conditions.

AI Disclosure

We may use artificial intelligence (AI) or other automated tools to support parts of our recruitment process. No automated tools make hiring decisions.