Full Stack Web Developer

We are seeking a highly skilled AI Python Developer with strong expertise in Machine Learning, Deep Learning, Data Analytics, and Data Science to design, develop, and deploy intelligent solutions. The role involves building and training predictive models, leveraging large-scale datasets, integrating AI-powered services with applications, and optimizing algorithms for performance and scalability. Candidates should have hands-on experience with Python-based ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn, etc.), statistical modeling, and data visualization techniques. The ideal candidate must also be proficient in working with structured and unstructured data, developing and consuming Open APIs, and deploying AI solutions on cloud platforms. Strong problem-solving abilities, mathematical/statistical foundations, and a passion for innovation in AI-driven technologies are essential. Key Responsibilities: Design, implement, and optimize machine learning and deep learning models for real-world applications. Perform data collection, preprocessing, cleaning, and feature engineering on large datasets. Build and integrate AI-driven APIs and services for scalable applications. Develop data pipelines and ensure seamless flow between data sources, models, and applications. Conduct data analytics, visualization, and reporting to derive actionable insights. Deploy AI/ML models on cloud environments (AWS, GCP, Azure) ensuring performance and scalability. Stay up to date with emerging AI/ML research, tools, and best practices to enhance solutions. Required Skills & Qualifications: Strong proficiency in Python and ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn, Keras). Experience with data analytics, visualization libraries (Pandas, NumPy, Matplotlib, Seaborn, Plotly). Solid understanding of machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers), and NLP techniques. Hands-on experience with SQL & NoSQL databases and data pipelines. Knowledge of RESTful & Open APIs integration. Familiarity with cloud-based AI deployments (AWS Sagemaker, GCP AI Platform, Azure ML). Strong mathematical/statistical background with focus on probability, optimization, and linear algebra. Excellent problem-solving, communication, and collaborative skills. Preferred Qualifications: Experience with MLOps tools (Docker, Kubernetes, MLflow, Airflow). Knowledge of Big Data technologies (Spark, Hadoop) is a plus. Prior experience in research or publication in AI/ML/DS fields. Required skills Front-end languages: HTML, CSS, and JavaScript.  Front-end frameworks: Experience with frameworks like React, Angular, or Vue.js is often required.  Back-end languages: Proficiency in languages such as Java, Python, Ruby, or PHP.  Databases: Experience with both SQL (like MySQL, PostgreSQL, Oracle) and NoSQL databases.  APIs: Experience in designing, developing, and integrating APIs.  Version control: Familiarity with version control systems like Git is essential.  Problem-solving: Strong analytical and problem-solving skills.  Communication: Good verbal communication skills are often necessary.