Key Responsibilities
- Develop and deploy scalable machine learning models for production environments
- Design and optimize data pipelines for training and inference
- Collaborate with data scientists to implement research models in production
- Monitor model performance and implement improvements for accuracy and efficiency
- Automate ML workflows using CI/CD pipelines and MLOps tools
- Ensure models meet latency, throughput, and reliability requirements
Requirements
- 3+ years of experience in machine learning engineering
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch)
- Experience with cloud platforms (AWS, GCP, or Azure)
- Knowledge of MLOps tools (Kubeflow, MLflow, Docker)
- Strong understanding of software engineering best practices