AI Engineer

This role is for one of the Weekday's clientsSalary range: Rs 600000 - Rs 800000 (ie INR 6-8 LPA)

AI Engineer

Requirements

Key Responsibilities

• AI Model Development: Design, implement, and train machine learning and deep learning models to solve business problems across different use cases.
• Data Preparation & Feature Engineering: Work with large and diverse datasets to collect, clean, preprocess, and transform data for model training and evaluation.
• Algorithm Optimization: Experiment with different algorithms, hyperparameters, and architectures to improve model performance and efficiency.
• Model Deployment & Integration: Collaborate with backend and DevOps teams to deploy AI models into production using frameworks like TensorFlow Serving, PyTorch, ONNX, or Docker.
• Research & Innovation: Stay up to date with advancements in AI research and tools. Apply innovative techniques from recent papers, open-source projects, or frameworks to improve business processes.
• Cross-Functional Collaboration: Work with product managers and software engineers to understand business requirements and translate them into technical solutions.
• Performance Monitoring: Evaluate models on real-world data, monitor drift, and continuously fine-tune and retrain models to maintain accuracy and reliability.
  

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or related field.
• 0-3 years of hands-on experience in machine learning, AI development, or data-driven software engineering.
• Proficiency in programming languages such as Python (preferred) or R, with experience using libraries like NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of machine learning algorithms, neural networks, data preprocessing, and statistical analysis.
• Experience with model evaluation metrics, data visualization tools (Matplotlib, Seaborn, Power BI), and version control systems like Git.
• Basic understanding of cloud platforms such as AWS, GCP, or Azure, especially their AI/ML services.
• Familiarity with APIs, REST frameworks, and data pipelines is a plus.
• Excellent problem-solving ability, curiosity, and eagerness to learn emerging AI technologies.
  

Preferred Qualifications

• Exposure to NLP (transformers, text classification, embeddings) or Computer Vision (CNNs, object detection).
• Internship or project experience involving AI/ML model deployment or end-to-end data workflows.
• Knowledge of MLOps tools (e.g., MLflow, Kubeflow) or containerization using Docker