Key Responsibilities
- Develop and deploy AI/ML models for production environments with a focus on scalability and reliability
- Design and implement MLOps pipelines for model training, versioning, and deployment
- Optimize AI workloads for performance, cost, and resource efficiency
- Collaborate with data science teams to integrate models into applications
- Monitor and maintain AI systems for drift detection and continuous improvement
Requirements
- 5+ years of experience in AI/ML engineering or related fields
- Strong proficiency in Python, TensorFlow, and MLOps tools
- Experience with Kubernetes, Docker, and cloud platforms (AWS/GCP)
- Knowledge of model serving, monitoring, and CI/CD for AI systems
- Problem-solving mindset with a focus on automation and efficiency