
Artificial Intelligence Engineer
2 weeks ago
Our team seeks a highly skilled MLOPS Data Scientist to drive the development and deployment of machine learning models that deliver business value.
Key Responsibilities:
- Design, train, validate and deploy predictive and analytical models using machine learning techniques.
- Collaborate with data engineers and business stakeholders to define data requirements and success metrics.
- Implement ML Ops best practices for model deployment, monitoring and maintenance.
- Build automated pipelines for model training, testing and retraining.
- Optimize model performance and ensure scalability and reliability.
- Monitor model drift, performance degradation and implement continuous improvement strategies.
- Develop and maintain CI/CD pipelines for machine learning workflows.
Required Skills and Qualifications:
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
- Experience with ML Ops tools/frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI or Azure ML).
- Familiarity with containerization and orchestration (Docker, Kubernetes).
- Knowledge of cloud platforms (AWS, GCP or Azure) for ML model deployment.
- Strong background in statistics, machine learning algorithms and model evaluation techniques.
- Familiarity with version control (Git) and CI/CD pipelines.
Benefits:
We offer a dynamic work environment, opportunities for growth and professional development, and a competitive compensation package.
Others:
Must have a Bachelor's/Master's degree in Computer Science, Data Science, Statistics or related field.
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