Software Engineer - AI/ML

We are looking for a highly skilled AI/ML & Data Engineer with strong technical expertise, excellent communication skills, and the ability to engage with clients and drive opportunities toward closure. The ideal candidate will combine hands-on engineering capabilities with strong business acumen - someone who can understand complex client requirements, architect the right solution, present it confidently, and help convert opportunities into successful projects.

Core Responsibilities

• Develop, train, test, and optimize machine learning models for real-world applications.
• Perform data collection, cleaning, preprocessing, and feature engineering to prepare datasets for model development.
• Implement machine learning and deep learning algorithms to solve business problems.
• Develop AI-powered applications using Large Language Models (LLMs), prompt engineering, and Generative AI techniques.
• Build and integrate Retrieval-Augmented Generation (RAG) pipelines and work with embeddings and vector databases where required.
• Evaluate model performance using appropriate metrics and improve accuracy, efficiency, and reliability.
• Integrate AI/ML models into applications using REST APIs and backend services.
• Assist in deploying models to production and maintaining their performance.
• Collaborate with software engineers, product teams, and other stakeholders to deliver AI-driven solutions.
• Maintain clean, reusable, and well-documented code while following software development best practices.
• Stay updated with emerging AI/ML technologies, frameworks, and industry trends.

Qualification

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• At least 1 year of hands-on experience in AI/ML development through professional employment or relevant practical experience.
• Experience working on AI/ML projects, with the ability to explain the approach, implementation, and results.
• Understanding of the machine learning development lifecycle, from data preparation to model evaluation and deployment.
• Ability to troubleshoot technical issues and work collaboratively within a team.

Requirements

• Proficiency in Python programming and object-oriented programming concepts.
• Working knowledge of NumPy, Pandas, and Scikit-learn.
• Understanding of supervised and unsupervised learning algorithms.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
• Basic experience with Generative AI, LLMs, prompt engineering, or AI APIs.
• Familiarity with REST APIs, Git, and model deployment practices.