AI/ML Developer

AI/ML Developer Position Description: The AI/ML Developer is to develop, train, validate, and deploy AI and ML models that meet the project's analytical needs, ensuring accuracy, scalability, and efficiency. Role & responsibilities Data Processing & Analysis Collect, clean, and preprocess structured and unstructured data. Conduct exploratory data analysis to identify trends and patterns. Model Development Design, train, validate, and fine-tune machine learning models using frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face. Develop and optimize deep learning architectures for classification, regression, NLP, or computer vision tasks. Deployment & Integration Deploy models using tools like Docker, FastAPI, Flask, or TensorFlow Serving. Integrate models into existing applications, pipelines, or APIs. Implement monitoring and performance evaluation of deployed models. Documentation & Collaboration Write clear and comprehensive documentation for models, data pipelines, and APIs. Work collaboratively with data engineers, software developers, and domain experts to ensure alignment with project objectives. Innovation & Research Stay up to date with the latest AI/ML research and tools. Contribute to prototyping and innovation initiatives within the organization. Deliverables: Clean, well-documented code and model scripts. Trained and validated AI/ML models with performance reports. Data pipelines and preprocessing scripts. Deployment-ready models integrated with APIs or platforms. Monthly progress reports on development and outcomes. Final report with documentation on model architecture, datasets, results, and recommendations. Preferred candidate profile Education: Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Experience: Minimum 3 years of experience in machine learning or AI development Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn. Experience with data preprocessing, feature engineering, and model evaluation. Experience with cloud services (AWS, Azure, GCP) for AI model deployment, good understanding of data structures, algorithms, and software engineering practices Experience with database systems (SQL, NoSQL) and big data tools (e.g., Spark, Hadoop) is a plus. Personal Qualities: Strong analytical and problem-solving skills. Excellent programming and debugging abilities. Ability to communicate technical concepts to non-technical stakeholders. Attention to detail and commitment to reproducible research/code. Strong teamwork and collaborative mindset.