Job Opportunities API

Mid-/Senior-level | Golang | .NET | Azure | Artificial Intelligence  At Genetec, we create exceptional outcomes for our customers with innovative strategies and software technologies that will keep their security environment robust and resilient. As a global leader in video surveillance software, the drive to go beyond expectations has been key to the Genetec experience since day one. Why this role matters  This role turns our AI strategy into reality. By modernising our ML and GenAI stack, enabling data workflows and experimentation, and building scalable inference platforms, you’ll help teams create quality datasets, evaluate models, and move them to production. Your work will make AI deployments faster, more reliable, and easier to improve - reducing risk and cost while accelerating innovation.  The team  You’ll join a newly created, diverse team across Canada, France, and Poland, ready to grow. Bring your passion for technology, development, quality, and automation to a collaborative group that shares ideas openly. You’ll help shape our products and build the foundation for AI-driven innovation, making a real impact.  What your day will look like Enable cheap ownership and evolution of high-quality datasets  Build and maintain self-service data acquisition, annotation, transformation, and versioning capabilities so developers and data practitioners can move from raw data to clean, versioned datasets quickly and continuously.  Facilitate data lineage tracking and data governance.  Provide tooling to build transformation pipelines with integrated data quality checks.  Facilitate experimentation with data and models  Enable researchers to track their experiments and reproduce past runs with minimal effort.  Provide access to services with compute clusters for running model training pipelines and experiments.  Facilitate full traceability of data, code, and artifacts across experiments and data transformation pipelines. Support deployment, scaling, and observability of models  Design and operate secure, automated deployment workflows that move models from experimentation to production in minutes, not weeks.  Implement continuous deployment pipelines with versioning and parallel deployments to ensure quality and enable rollbacks.  Optimise runtime environments to meet latency and performance targets, supporting multi-cluster and multi-tenant scaling.   Requirements About you  We welcome all qualified candidates, including those who may not meet every listed requirement. If you're excited about this role and believe you can make an impact, we’d love to hear from you.  Machine Learning & MLOps  Hands-on experience with MLFlow, KServe, AirFlow.  Knowledge on labelling/annotation tooling  Experience with experiment tracking tools  Familiarity with model runtimes and deployment (Triton Inference Server, OpenVino Model Server).  Knowledge of DevOps, CI/CD for ML, GitOps workflows, and automated deployment strategies.  Observability & Monitoring  Proficiency in telemetry and data drift and quality monitoring.  Cloud & Infrastructure  Strong skills in Kubernetes and Terraform for infrastructure automation.  Experience with scaling services in cloud environments.  Programming & Automation  Solid coding skills in at least one language, Golang or .NET, and the motivation to learn Golang or .NET.     Ni