Job Title: MLOps EngineerWork Arrangement: RemoteLocation: Toronto, CanadaSalary: Up-to $125,000 CADMLOps Engineer – Real-Time AI SystemsWe're looking for an experienced MLOps Engineer to help deploy and scale cutting-edge ML models for real-time video and audio applications. You'll work alongside data scientists and engineers to build fast, reliable, and automated ML infrastructure.Key ResponsibilitiesBuild and manage ML pipelines for training, validation, and inference.Automate deployment of deep learning and generative AI models.Ensure model versioning, rollback, and reproducibility.Deploy models on AWS, GCP, or Azure using Docker and Kubernetes.Optimize real-time inference using TensorRT, ONNX Runtime, or PyTorch.Use GPUs, distributed systems, and parallel computing for performance.Create CI/CD workflows (GitHub Actions, Jenkins, ArgoCD) for ML.Automate model retraining, validation, and monitoring.Address data drift, latency, and compliance concerns.What You Bring3+ years in MLOps, DevOps, or model deployment roles.Strong Python and experience with ML frameworks (PyTorch, TensorFlow, ONNX).Proficiency with cloud platforms, Docker, and Kubernetes.Experience with ML tools like MLflow, Airflow, Kubeflow, or Argo.Knowledge of GPU acceleration (CUDA, TensorRT, DeepStream).Understanding of scalable, low-latency ML infrastructure.Nice to HaveExperience with Ray, Spark, or edge AI tools (Triton, TFLite, CoreML).Basic networking knowledge or CUDA programming skills.
Harry Crick