AI/ML Engineer

Job Summary 

The AI/ML Engineer will be responsible for designing, developing, training, testing, and deploying machine learning and artificial intelligence models to solve business problems. The role involves working closely with product, engineering, and domain teams to build scalable AI-driven solutions. 

Key Responsibilities 

• Design, develop, and optimize machine learning and deep learning models. 
• Build AI pipelines for data preprocessing, feature engineering, training, validation, and deployment. 
• Develop NLP, computer vision, predictive analytics, recommendation systems, or generative AI solutions depending on business needs. 
• Work with large datasets and perform exploratory data analysis. 
• Integrate AI/ML models into production systems and APIs. 
• Monitor model performance, retrain models, and improve accuracy over time. 
• Collaborate with cross-functional teams to understand business requirements. 
• Ensure data quality, model explainability, and ethical AI practices. 
• Maintain documentation for models, experiments, and deployment processes. 

Required Skill Set 

• Strong programming skills in Python. 
• Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost. 
• Knowledge of NLP, Computer Vision, Deep Learning, and Generative AI. 
• Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI. 
• Experience with SQL, NoSQL databases, and data preprocessing. 
• Strong understanding of statistics, linear algebra, and probability. 
• Knowledge of cloud platforms such as AWS, Azure, or GCP. 
• Experience with Docker, Kubernetes, and CI/CD pipelines. 
• Familiarity with REST APIs and microservices. 

Qualifications 

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field. 
• 2–8 years of relevant experience in AI/ML development. 
• Relevant certifications in AI/ML or cloud technologies are preferred.