Sr. AI~ML Engineer

As a Senior AI/ML Engineer/Team Lead at Aaizel Tech, you will lead the design, development, and deployment of advanced Machine Learning models and AI solutions. Your role will involve working on a variety of projects ranging from predictive analytics and NLP to computer vision and anomaly detection. Additionally, you will have the opportunity to mentor a team of AI/ML professionals, collaborate with cross-functional teams, and drive innovation by integrating cutting-edge research with scalable production systems. Key Responsibilities: - Model Development & Optimization - Design & Implementation: - Architect and develop end-to-end ML solutions for applications such as predictive analytics, anomaly detection, computer vision, and NLP. - Utilize advanced techniques including deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) to address complex challenges. - Optimization: - Fine-tune model parameters using techniques such as hyperparameter tuning (Grid Search, Bayesian Optimization, Neural Architecture Search). - Optimize models for both accuracy and inference speed to meet real-time processing requirements. - Advanced Data Engineering & Integration - Data Pipeline Development: - Build robust ETL pipelines using libraries like Pandas, NumPy, and PySpark to process large-scale datasets from satellite imagery, IoT sensors, and real-time streams. - Integrate data from diverse sources (APIs, databases, big data platforms like Hadoop and Apache Kafka) to support real-time analytics. - Data Quality & Preprocessing: - Implement data cleansing, feature engineering, and transformation pipelines to ensure high-quality inputs for ML models. - Research & Innovation - Algorithm Research: - Conduct research on state-of-the-art ML techniques including Transfer Learning, Transformer models, and AutoML to enhance model performance. - Innovate new algorithms for specialized tasks such as geospatial analysis, environmental modeling, or cybersecurity threat detection. - Prototyping & Experimentation: - Develop proof-of-concept models and prototypes to validate new approaches before production deployment. - Deployment, MLOps & Performance Monitoring - Model Deployment: - Deploy models using containerization (Docker) and orchestration tools (Kubernetes) to ensure scalable and efficient production environments. - Work with cloud platforms (AWS, Azure, GCP) and model serving solutions (TensorFlow Serving, ONNX, TorchServe) for high-throughput inference. - MLOps & Lifecycle Management: - Implement CI/CD pipelines for ML models, ensuring seamless updates and versioning. - Develop monitoring dashboards (using Prometheus, Grafana) to track model performance and trigger retraining based on real-time feedback. - Collaboration & Leadership - Cross-Functional Teamwork: - Collaborate closely with data engineers, software developers, domain experts, and product managers to integrate AI solutions into end-to-end products. - Mentorship & Code Quality: - Provide technical leadership and mentorship to junior AI/ML engineers, ensuring adherence to coding standards and best practices. - Participate in code reviews, maintain detailed documentation, and foster a culture of continuous learning. In addition to the above responsibilities, the recommended technology stack at Aaizel Tech includes: - Backend Framework: Python (Django/FastAPI) - AI/ML Frameworks: PyTorch + Hugging Face Transformers + scikit-learn - Data Engineering: Apache Kafka + Apache Spark + Apache NiFi - Database & Storage: PostgreSQL with TimescaleDB extension - DevOps & Monitoring: Docker, Kubernetes, GitLab CI/CD, Prometheus/Grafana This is an exciting opportunity to be part of a pioneering tech startup and contribute to cutting-edge projects in a dynamic environment. As a Senior AI/ML Engineer/Team Lead at Aaizel Tech, you will lead the design, development, and deployment of advanced Machine Learning models and AI solutions. Your role will involve working on a variety of projects ranging from predictive analytics and NLP to computer vision and anomaly detection. Additionally, you will have the opportunity to mentor a team of AI/ML professionals, collaborate with cross-functional teams, and drive innovation by integrating cutting-edge research with scalable production systems. Key Responsibilities: - Model Development & Optimization - Design & Implementation: - Architect and develop end-to-end ML solutions for applications such as predictive analytics, anomaly detection, computer vision, and NLP. - Utilize advanced techniques including deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) to address complex challenges. - Optimization: - Fine-tune model parameters using techniques such as hyperparameter tuning (Grid Sea