AI Engineer

Job Summary We are looking for a motivated and technically strong AI Engineer to join our engineering team. The ideal candidate will work on developing, testing, and deploying AI and machine learning solutions for real-world business applications. This role is suitable for fresh graduates and candidates with 0

3 years of experience who have a strong foundation in programming, mathematics, machine learning, and artificial intelligence. Key Responsibilities Develop and implement machine learning and AI models for business and technical applications. Collect, clean, preprocess, and analyze structured and unstructured datasets. Build, train, evaluate, and optimize machine learning models. Apply algorithms for classification, regression, clustering, recommendation, and prediction problems. Work with Python libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch. Assist in developing Generative AI and LLM-based applications, including prompt engineering and AI-powered workflows. Work with APIs and integrate AI/ML models into software applications. Perform exploratory data analysis and feature engineering. Evaluate model performance using appropriate metrics and validation techniques. Fine-tune and optimize models based on business requirements and performance results. Assist in deploying AI/ML models into development or production environments. Collaborate with software engineers, data scientists, product teams, and business stakeholders. Document model development, experiments, results, and technical processes. Research emerging AI technologies and evaluate their potential applications. Participate in code reviews, testing, debugging, and continuous improvement activities. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, Statistics, Electronics, or a related technical field. 0

3 years of experience in AI, machine learning, data science, or software development. Strong programming knowledge in Python. Good understanding of machine learning fundamentals and algorithms. Knowledge of data structures, algorithms, and object-oriented programming. Strong understanding of basic mathematics and statistics. Experience with libraries such as Pandas, NumPy, and Scikit-learn. Basic understanding of model training, validation, and performance evaluation. Strong analytical and problem-solving skills. Good communication and teamwork skills. Willingness to learn new AI technologies and frameworks. Preferred Qualifications Academic projects, internships, or personal projects involving AI/ML. Knowledge of TensorFlow, PyTorch, Keras, or Hugging Face. Understanding of Deep Learning, NLP, Computer Vision, or Generative AI. Familiarity with Large Language Models (LLMs), embeddings, vector databases, RAG, and prompt engineering. Basic knowledge of cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with Git, Docker, APIs, and basic CI/CD concepts. Knowledge of SQL and database technologies. Experience deploying models using Flask, FastAPI, Streamlit, or similar frameworks. Relevant AI/ML certifications are an advantage. Key Skills Python Machine Learning Artificial Intelligence Data Analysis Deep Learning Generative AI LLMs NLP / Computer Vision Pandas & NumPy Scikit-learn TensorFlow / PyTorch SQL Problem-solving Analytical thinking What We Offer Hands-on experience working on real-world AI and machine learning projects. Training and mentorship from experienced AI/ML professionals. Exposure to Generative AI, LLMs, machine learning, and cloud technologies. Opportunity to build and deploy AI-powered applications. Career growth opportunities based on technical skills and performance. Professional and collaborative work environment. Ideal Candidate The ideal candidate is a curious, analytical, and technically driven professional who is passionate about Artificial Intelligence and enjoys solving complex problems using data and technology. Candidates should have strong Python and machine learning fundamentals and a willingness to continuously learn and experiment with emerging AI technologies.