- Design, implement, and maintain CI/CD pipelines for machine learning workflows using tools like GitHub Actions, Azure DevOps, or Jenkins.
- Build and optimize data processing pipelines in Apache Spark (PySpark and Scala) for large-scale, distributed listener datasets.
- Deploy and manage Databricks environments, ensuring efficient cluster usage, job scheduling, and cost optimization.
- Collaborate with data scientists to productionize ML models, integrating them into scalable APIs or batch processing systems that feed real-time, machine-readable audience signals.
- Implement automated testing, monitoring, and alerting for ML pipelines to ensure the reliability and reproducibility that certified buyers require.
- Champion best practices in version control, model registry management, and environment reproducibility.
- Help evolve our listener data infrastructure toward agent-compatible supply — live, structured, queryable data feeds that autonomous buying systems can discover and act on without human mediation.
- Proven experience in Data Engineering, MLOps, and DevOps roles with a focus on automation and scalability.
- Strong programming skills in Python, with hands-on experience in Apache Spark. Scala is a huge plus.
- Advanced expertise in Databricks, including Delta Lake, structured streaming, feature engineering
- Solid understanding of CI/CD principles and tools (e.g., GitHub Actions, Jenkins, Azure DevOps, GitLab CI, ArgoCD).
- Familiarity with cloud platforms (AWS, Azure, or GCP) for data and ML workloads.
- A problem-solving mindset and the ability to work closely with cross-functional teams.
- Strong architectural mindset, capable of evaluating trade-offs across cost, performance, scalability, and maintainability when selecting tools and designing systems.
- Experience working with containerized and orchestrated environments (Kubernetes / OpenShift), including deployment, scaling, and fault tolerance of data and ML workloads.
- Advanced English required. French is an asset.
- Familiarity with IAB data standards, programmatic advertising infrastructure, or AdTech data pipelines is a strong asset.
- Fully remote position (must be based in ONTARIO or QUEBEC)
- 4 weeks of vacation + 5 paid personal days annually
- Group insurance programs as of your first day, including access to telemedicine and an EAP
- Collective RRSP with matching contribution
- Internet reimbursement and more
- Budget $100-125k CAD
Skills Required
- Based in Ontario or Quebec
- Proven experience in data engineering, MLOps, and DevOps roles focused on automation and scalability
- Strong Python programming skills
- Hands-on experience with Apache Spark
- Advanced expertise in Databricks, including Delta Lake, structured streaming, and feature engineering
- Solid understanding of CI/CD principles and tools
- Familiarity with AWS, Azure, or GCP cloud platforms
- Experience with containerized and orchestrated environments, including Kubernetes or OpenShift
- Advanced English proficiency
- Scala experience
- French proficiency
- Familiarity with IAB data standards, programmatic advertising infrastructure, or AdTech data pipelines
What We Do
Triton Digital® is the global technology and services leader to the digital audio and podcast industry. Operating in more than 80 countries, Triton provides innovative technology that enables broadcasters, podcasters, and online music services to build their audience, maximize their revenue, and streamline their day-to-day operations. In addition, Triton powers the global online audio industry with Webcast Metrics®, the leading online audio measurement service and Podcast Metrics, one of the first IAB certified podcast measurement services in the industry. With unparalleled integrity, excellence, teamwork, and accountability, Triton remains committed to connecting audio, audience, and advertisers to continuously fuel the growth of the global online industry. For more information, visit www.TritonDigital.com.









