Full Stack Engineer

Project Role : Full Stack Engineer
Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset.
Must have skills : Machine Learning
Good to have skills : Cloud Infrastructure, Gen AI
Minimum 5 year(s) of experience is required
Educational Qualification : 15 Years of full time education

Machine Learning Engineer Job Description A Machine Learning Engineer is a professional who is skilled and specializes in designing and developing machine learning systems, possess expertise in statistics, programming, and data science. The role involves creating efficient self-learning applications and contributing to advancements in artificial intelligence. Qualifications: Strong programming skills (Python, R, or similar languages). Knowledge of data science concepts, including feature engineering, model evaluation, and validation. Expertise in statistics and understanding of machine learning algorithms. Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch). Experience with cloud platforms (AWS, Google Cloud, Azure) for model deployment. Ability to work collaboratively in cross-functional teams. Responsibilities: ? Study and Transform Data Science Prototypes: Work with data to create models, perform statistical analysis, and train and retrain systems to optimize performance. Explore and preprocess data, ensuring its suitable for machine learning tasks. Design Machine Learning Systems: Design and construct sophisticated machine learning models. Choose appropriate algorithms and architectures based on the problem domain and data characteristics. ? Research and Implement ML Algorithms and Tools: Staying updated with the latest developments in the field, they explore new algorithms and tools. Implement machine learning algorithms, adapting them to specific use cases. Develop Machine Learning Applications: Build applications that leverage machine learning models. Collaborate with software engineers to integrate ML components into larger systems. Deploy and Maintain Machine Learning Models Ensure scalability and reliability, they deploy models in cloud platforms such as AWS. Regular performance evaluations, identifying bottlenecks, and implementing optimization strategies. Passionate about pushing the boundaries of AI technology and creating innovative self-learning applications, consider joining our team as a Machine Learning Engineer!