AI Engineer

Position Summary

We are seeking a talented AI Engineer to design and maintain scalable ML data pipelines and optimize MLOps infrastructure. This remote position offers an exciting opportunity to collaborate with cross-functional teams to bring AI models from experimentation to production.

Responsibilities

• Design, build, and maintain scalable data pipelines for ML workloads
• Manage and optimize MLOps infrastructure including model training, versioning, and deployment pipelines
• Monitor model performance in production and implement retraining workflows
• Collaborate with data scientists and software engineers to move models from experimentation to production
• Maintain CI/CD pipelines for ML systems and ensure reliability and scalability

Requirements

• 2-5 years of experience in AI/ML engineering
• Strong proficiency in Python
• Hands-on experience with ML frameworks such as PyTorch or TensorFlow
• Experience building and maintaining data pipelines for ML workloads
• Practical MLOps experience including model deployment, monitoring, and versioning
• Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, or Azure ML)
• Familiarity with orchestration tools such as Airflow, Prefect, or Kubeflow
• Experience with containerization (Docker, Kubernetes)
• Knowledge of feature stores and experiment tracking tools (MLflow, Weights & Biases)