AI/ML Intern

Job Description: AI/ML Engineer Location: Gurgaon, Haryana, India Position: AI/ML Engineer -Intern Stipend: As per industry standards About Aaizel Tech Aaizel Tech is a pioneering tech startup at the intersection of cybersecurity, AI, geospatial solutions, and more. We drive innovation by delivering transformative technology solutions across industries. As part of our dynamic team, you'll gain hands-on experience and learn from experts who are dedicated to pushing the boundaries of what's possible. Key Responsibilities Model Development and Optimization: Design, implement, and deploy ML models for diverse applications, including predictive analytics, anomaly detection, and computer vision, tailored for cybersecurity, climate monitoring, and geospatial data analysis. Utilize deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) for complex problem-solving. Advanced Data Engineering: Develop ETL pipelines and preprocessing scripts using Pandas, Numpy, and PySpark to handle large datasets from satellite imagery, IoT sensors, and real-time data sources. Integrate data from APIs, databases, and big data platforms (Hadoop, Apache Kafka) to support real-time analytics. Algorithm Research and Development: Research state-of-the-art ML techniques, including Transfer Learning, Transformer models, and AutoML, to enhance model performance. Innovate new algorithms for geospatial analysis, such as object detection on aerial imagery, spatial clustering, and environmental modeling. Deployment and MLOps: Deploy models using Docker, Kubernetes, and CI/CD pipelines, ensuring robust model lifecycle management. Work with cloud platforms (AWS, Azure, GCP) to implement scalable model serving solutions, using technologies like Sage Maker, TensorFlow Serving, and ONNX. Performance Evaluation and Tuning: Perform model evaluation using advanced metrics (F1 Score, AUC-ROC, Intersection over Union for spatial data) and optimize for both accuracy and inference speed. Implement hyperparameter tuning using Bayesian Optimization, Grid Search, and Neural Architecture Search. Performance Evaluation and Tuning: Perform model evaluation using advanced metrics (F1 Score, AUC-ROC, Intersection over Union for spatial data) and optimise for both accuracy and inference speed. Implement hyperparameter tuning using Bayesian Optimization, Grid Search, and Neural Architecture Search. 7. Collaboration and Code Quality: Collaborate with data engineers, cybersecurity experts, and geospatial analysts to integrate ML solutions into end-to-end products. Adhere to coding standards, participate in code reviews, and maintain high-quality codebases using Git, Jira, and Confluence. Monitoring and Maintenance: Develop monitoring dashboards using Grafana, Prometheus, or similar tools to track model performance post-deployment. Implement feedback loops for model retraining based on real-time data and evolving application needs. Required Skills, Qualification And Experience Educational Background: Bachelor’s/Master’s in Computer Science, Data Science, Machine Learning, or a related field from preferably top-tier institutions. Technical Proficiency: Strong skills in Python, PyTorch, TensorFlow, and Scikit-learn. Proficiency in SQL, NoSQL databases (MongoDB, Cassandra), and data warehousing solutions (Redshift, BigQuery). Problem-Solving: Analytical mindset with the ability to solve complex problems using data-driven approaches. Communication: Capable of translating technical details into actionable insights for diverse stakeholders. Adaptability: Ability to thrive in a high-paced, dynamic startup environment with a focus on rapid iteration and delivery. Skills:- Scikit-Learn, TensorFlow, PyTorch, Machine Learning (ML), Artificial Intelligence (AI) and Convolutional Neural Network (CNN)