Job Title: MLOps Engineer

Work Arrangement: Remote

Location: Toronto, Canada

Salary: Up-to $125,000 CAD

MLOps Engineer – Real-Time AI Systems

We'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 Responsibilities

• Build 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 Bring

• 3+ 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 Have

• Experience with Ray, Spark, or edge AI tools (Triton, TFLite, CoreML).
• Basic networking knowledge or CUDA programming skills.