This role is for a seasoned AIML Engineer focused on building and refining machine learning systems across multiple domains. You will lead the development of models using deep learning, natural language processing, and traditional ML techniques, ensuring high accuracy and scalability. Your work will center on improving model performance through feature engineering, data augmentation, and optimization strategies.
Key Responsibilities
- Design, train, and refine machine learning and deep learning models using Python-based tools and frameworks
- Apply advanced data handling techniques with SQL to prepare and manage large-scale datasets
- Iterate on model architecture and inputs to enhance predictive accuracy and efficiency
- Deploy models into production environments, ensuring reliability and integration with existing systems
- Collaborate across teams to support end-to-end model lifecycle management
Required Expertise
- 5 to 14 years of hands-on experience in machine learning model development
- Proficiency in Python and key libraries including scikit-learn, XGBoost, and Keras
- Demonstrated success in improving model accuracy through feature selection and engineering
- Solid background in deploying models into production and maintaining their performance over time
- Experience working with NLP, deep learning, and data preprocessing workflows
Work Environment
This position operates in a hybrid work model, offering flexibility to support a sustainable work-life balance. You’ll be part of a global, collaborative network where innovation and personal growth are prioritized. The organization fosters an inclusive, responsible culture that encourages rethinking what’s possible in technology and society.
Professional Development
- Access to training and certifications in cutting-edge AIML technologies
- Opportunities for career advancement and skill expansion
- Support for continuous learning and exploration of emerging technical domains
