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 :
• 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 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.

(ref : hirist.tech)