AI Engineer

Job description

Roles and responsibilities:

1. Problem Identification & Requirement Analysis

* Understand business problems and identify how AI can provide solutions.

* Work with stakeholders to define AI project scope and objectives.

* Translate business needs into technical AI models.

2. Data Collection & Preprocessing

* Collect data from multiple sources (databases, APIs, sensors, etc.).

* Clean, preprocess, and transform raw data for model training.

* Handle missing data, outliers, and data imbalance issues.

3. Model Development

* Design and develop Machine Learning (ML) and Deep Learning (DL) models.

* Select appropriate algorithms (regression, classification, clustering, etc.).

* Build AI models using frameworks like TensorFlow, PyTorch, or Scikit-learn.

* Develop NLP, Computer Vision, or Generative AI solutions when required.

4. Model Training & Evaluation

* Train models using large datasets.

* Tune hyperparameters for better performance.

* Evaluate models using metrics like accuracy, precision, recall, F1-score.

* Perform cross-validation and testing.

5. Deployment & Integration

* Deploy AI models into production environments.

* Integrate AI solutions with web apps, mobile apps, or enterprise systems.

* Work with DevOps teams for CI/CD pipelines.

6. Model Optimization & Monitoring

* Monitor model performance after deployment.

* Retrain models when performance drops (model drift handling).

* Optimize models for speed, scalability, and cost.

7. Research & Innovation

* Stay updated with latest AI trends and technologies.

* Experiment with new algorithms and techniques.

* Conduct research to improve existing models.

8. Collaboration & Documentation

* Work with data scientists, software developers, and business teams.

* Document models, processes, and workflows.

* Present AI solutions and findings to stakeholders.

9. Ethical AI & Security

* Ensure responsible AI usage and data privacy compliance.

* Reduce bias in AI models.

* Maintain model transparency and explainability.

Key Skills Required

* Strong knowledge of Python, R, or Java

* Machine Learning & Deep Learning concepts

* Data structures & algorithms

* Statistics & mathematics

* Cloud platforms (AWS, Azure, GCP)

* Problem-solving and analytical thinking