Full Stack Lead

You are a highly skilled Full Stack Lead with Python expertise and a strong background in Machine Learning. Your role involves designing, developing, and implementing cutting-edge solutions using unsupervised learning methods. You have hands-on experience with various ML algorithms and frameworks, along with a solid understanding of data processing and analysis. Your key responsibilities include designing and implementing scalable web applications and platforms using technologies such as Typescript, NestJS, Angular, NodeJS, ExpressJS, TypeORM, and Postgres. It is essential to have a good understanding of web and REST API design patterns. Experience with AWS technologies like EKS, ECS, ECR, Fargate, EC2, Lambda, ALB will be advantageous. You must also have hands-on experience with unit test frameworks like Jest and a good working knowledge of JIRA, Confluence, and Git. Having a basic knowledge of Kubernetes and Terraform for infrastructure as code, Docker compose, and Docker is required. You should demonstrate a strong understanding of microservices architecture and the ability to implement components independently. Your problem-solving skills, excellent communication skills, and the ability to develop, test, and maintain robust Python code for machine learning applications are crucial. Your tasks also involve implementing unsupervised learning algorithms, collaborating with cross-functional teams, performing data preprocessing, feature extraction, and data augmentation, as well as designing and conducting experiments to validate and optimize unsupervised learning models. You will utilize ML libraries and frameworks like Scikit-learn, TensorFlow, and PyTorch to build and deploy models. Documenting and presenting findings and insights to stakeholders in a clear and concise manner is also part of your responsibilities. To qualify for this role, you need a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. Proven experience as a Python Developer with a strong portfolio of ML projects is essential. In-depth knowledge of unsupervised learning techniques, proficiency in Python and ML libraries, experience with data preprocessing and transformation techniques, and a strong understanding of statistics, probability, and linear algebra are required. Your ability to work independently and as part of a team in a fast-paced environment, excellent problem-solving skills, attention to detail, and strong communication skills, both written and verbal, are important. Preferred qualifications include experience with big data technologies, familiarity with cloud platforms like AWS, knowledge of deep learning architectures and frameworks, prior experience in relevant industries, and publications or contributions to open-source ML projects. Your primary skill set should include Full stack, Python, and AI/ML.,