MLOps Developer

Responsibilities :

- Determine and develop user requirements for ML systems in production to ensure maximum usability and performance.

- Design and implement CI/CD pipelines for ML model training, testing, and deployment.

- Collaborate with data scientists, ML engineers, and software developers to operationalize ML models.

- Automate and optimize workflows for data preprocessing, feature engineering, and model serving.

- Monitor ML models in production for performance, drift, and reliability, implementing retraining strategies as needed.

- Ensure compliance with data governance, security, and regulatory standards.

- Document workflows, processes, and system architecture to ensure transparency and reproducibility.

Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, or related field.

- 3-7 years of experience in MLOps, Machine Learning Engineering, or DevOps for AI systems.

- Strong knowledge of cloud platforms (AWS, Azure, or GCP) and containerization tools like Docker/Kubernetes.

- Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and orchestration tools (Airflow, Kubeflow, MLflow).

- Proficiency in scripting and programming (Python, Shell, or similar).

- Excellent communication skills and ability to collaborate across multidisciplinary teams.

- Strong problem-solving, analytical, and critical thinking abilities.