AI/ML Engineer

We are seeking a skilled AI/ML Engineer with hands-on experience in developing, optimizing, and deploying machine learning, deep learning, and NLP models. The ideal candidate will have strong expertise in data handling, model engineering, and production deployment, contributing to AI-driven solutions across multiple domains.

Key Responsibilities :

- Design, develop, and implement ML, deep learning, and NLP models to address complex business problems.

- Perform end-to-end model development including data preprocessing, feature engineering, model selection, training, evaluation, and optimization.

- Handle large datasets efficiently using SQL and other data management tools.

- Improve model performance through feature engineering, feature selection, augmentation, and hyperparameter tuning.

- Deploy and monitor ML models in production environments, ensuring scalability and reliability.

- Collaborate with cross-functional teams to deliver actionable AI insights and solutions.

- Stay updated with the latest trends in AI/ML and NLP for continuous model improvement.

Required Skills and Qualifications :

- 5- 14 years of experience in developing and implementing ML, deep learning, and NLP models.

- Strong proficiency in Python and ML libraries/frameworks such as scikit-learn, XGBoost, TensorFlow/Keras, or PyTorch.

- Expert in data handling and querying using SQL and other tools.

- Proven experience in model engineering and improving model accuracy.

- Hands-on experience in deploying ML models to production with monitoring and performance tuning.

- Strong problem-solving skills and ability to apply ML techniques across domains.

Preferred Skills :

- Experience with cloud platforms (AWS, Azure, GCP) for model deployment.

- Knowledge of containerization and orchestration tools like Docker and Kubernetes.

- Familiarity with MLOps practices and automated model monitoring.

What We Offer :

- Work on cutting-edge AI/ML projects across diverse industries.

- Collaborative, innovative work environment with continuous learning opportunities.

- Competitive compensation and benefits.