Job Description
We are looking to add a ML Engineer to join our Karachi office.
Key Responsibilities:
- Deploy, monitor, and manage machine learning models in production environments.
- Develop and maintain scalable ML pipelines for training and inference.
- Automate model retraining and deployment using CI/CD workflows.
- Optimize cloud and on-prem infrastructure for ML workloads.
- Implement monitoring, logging, and alerting for model performance and drift detection.
- Ensure reproducibility, version control, and governance for ML models.
- Collaborate with data scientists to optimize model deployment strategies.
- Work with Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure) for model hosting.
- Manage feature stores, model registries, and data pipelines.
Required Skills & Qualifications:
- Bachelor's or Master’s degree in Computer Science, AI, Data Science, or a related field.
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with ML pipeline orchestration tools like Kubeflow, Airflow, or MLflow.
- Strong knowledge of DevOps & CI/CD practices for ML (Git, Jenkins, Docker, Kubernetes).
- Familiarity with cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
- Experience in model monitoring, logging, and automated retraining.
- Understanding of data engineering, feature stores, and ETL pipelines.
- Strong problem-solving and collaboration skills.
- Previous experience in applying machine learning to service sector domains, such as retail, hospitality, transportation, or similar, is a plus.
- Knowledge of cloud platforms (e.g AWS, Azure, GCP) and their machine learning services are advantageous.
- Excellent communication skills to convey technical concepts to diverse audiences effectively.