Machine Learning Engineer
- Published on
About the Role
We are searching for an experienced MLOps Engineer to join DeepRec.ai. The role will focus on deploying and scaling cutting-edge ML models for real-time video and audio applications. You will work with a dynamic team of data scientists and engineers to create reliable and efficient ML infrastructure that meets our requirements.
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.
- Utilize GPUs, distributed systems, and parallel computing to enhance performance.
- Create CI/CD workflows (GitHub Actions, Jenkins, ArgoCD) for ML.
- Address data drift, latency, and compliance concerns.
About the Candidate
Expectations:
- A minimum of 3 years of experience in MLOps, DevOps, or similar model deployment roles.
- Strong proficiency in Python and experience with ML frameworks (PyTorch, TensorFlow, ONNX).
- Proficiency with cloud platforms, Docker, and Kubernetes.
- Familiarity with ML tools like MLflow, Airflow, Kubeflow, or Argo.
- Strong understanding of GPU acceleration (CUDA, TensorRT, DeepStream) and scalable ML infrastructure.
Nice to Have:
- Experience with Ray, Spark, or edge AI tools (Triton, TFLite, CoreML).
- Basic networking knowledge or CUDA programming skills.
About the Company
DeepRec.ai specializes in designing advanced AI systems to tackle real-time challenges in video and audio processing. We pride ourselves on innovation and teamwork, continuously adapting to the latest developments in the field.
Company culture and benefits
We offer a collaborative and inclusive work environment where all team members can contribute ideas and grow professionally. Our compensation package includes a competitive salary up to $125,000 CAD, along with opportunities for career advancement and skill development.