Senior Platform Engineer, ML Data Systems

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Platform Engineer, ML Data Systems in Canada. As a Senior Platform Engineer specializing in ML Data Systems, you will be instrumental in designing, building, and maintaining scalable dataset management pipelines that power AI-driven learning systems. You will collaborate closely with data scientists, AI engineers, and platform teams to ensure that large-scale datasets are clean, consistent, and representative, enabling reliable model training and evaluation. This role spans data engineering, MLOps, and AI operations, with a focus on dataset quality, reproducibility, and governance. You will influence internal processes, contribute to shared tools and documentation, and help the team adopt best practices for managing sensitive data while supporting the mission to provide equitable, high-quality education worldwide. Accountabilities Evolve and maintain pipelines for transforming raw trace and educational data into ML-ready datasets. Clean, normalize, and enrich data while preserving semantic meaning and ensuring consistency. Prepare datasets for human labeling and integrate results into machine learning workflows. Develop and maintain scalable ETL pipelines using Airflow, DBT, Go, and Python on GCP. Implement automated testing and validation to detect data drift or labeling inconsistencies. Collaborate with AI engineers, platform developers, and product teams to define and implement data strategies. Contribute to internal tools, documentation, and governance strategies for secure and compliant data management. Requirements Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. 5+ years of software engineering experience, including 3+ years working with large ML datasets, particularly open-source repositories like Hugging Face. Strong programming skills in Go, Python, SQL, and experience with at least one data pipeline framework (Airflow, Dagster, Prefect). Familiarity with data versioning tools (e.g., DVC, LakeFS) and cloud storage systems. Understanding of ML workflows, including training data preparation and evaluation, as well as large language model architectures and capabilities. Attention to detail with a strong focus on data quality, reproducibility, and robustness. Experience with labeling platforms or human-in-the-loop systems is a plus. Knowledge of ML evaluation techniques, MLOps practices, and human-centered AI applications is desirable. Proven cross-cultural competency and commitment to diversity, equity, and inclusion. Benefits Competitive salary range of $186,306–$232,883 CAD (depending on experience). Remote-first work environment with flexible scheduling. Generous paid time off, including pre-scheduled wellness days. Comprehensive parental leave and wellness support. 401(k) plan with company matching and robust insurance options (medical, dental, vision, life). Opportunity to work on impactful AI and education projects that serve historically under-resourced communities. Supportive and inclusive team culture, with learning and development opportunities. Why Apply Through Jobgether? We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role’s core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best Data Privacy Notice By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. #J-18808-Ljbffr