Advanced ML Modeling learning applications. Collaborate with front-end and back-end developers to integrate machine learning models into web-based applications. Implement MLOps practices to streamline the machine learning lifecycle, including model versioning, deployment, and monitoring. Use tools such as DVC and MLflow to manage and track experiments, artifacts, and models. DevOps Integration Collaborate with DevOps teams to ensure seamless integration of machine learning models into production environments. Implement CI/CD pipelines for machine learning workflows. Algorithmic Innovation pipeline. Propose and implement novel approaches to improve model performance and efficiency. Classic Machine Learning & Mathematical Modelling Develop and implement classic machine learning algorithms such as linear regression, decision trees, and support vector machines to solve business problems. Design and optimize mathematical models for predictive analytics and forecasting, leveraging statistical methods and mathematical principles. Data Analytics & Feature Engineering Conduct thorough exploratory data analysis to uncover patterns, correlations, and trends in complex datasets, driving actionable insights. Lead the feature engineering process, including the creation, selection, and transformation Full Stack ML Engineering Utilize FastAPI and Streamlit to develop user-friendly and interactive machine learning applications. Algorithmic Innovation Stay abreast of the latest developments in classical machine learning, NLP, LLM, computer vision and deep learning, and contribute to the companys innovation pipeline. Here s what you will need to have to join the Ninja Clan Proficiency in Python and experience with relevant libraries and frameworks, including TensorFlow, PyTorch, OpenCV, FastAPI, Streamlit, DVC, and MLflow. Excellent problem-solving skills and the ability to work independently or collaboratively. Collaboration and Cross- Functional Teamwork Collaborate with machine learning engineers, data scientists, & software developer Provide mentorship and technical guidance to junior team members. Bachelors or Masters in Computer Science, Machine Learning, or a related field. Minimum of 3 years of proven experience in developing and deploying NLP solutions, computer vision, deep learning, and classical machine learning models. Strong understanding of classical ML techniques, mathematical modelling, statistical analysis, deep learning architectures and data platforms. Experience with MLOps practices and DevOps integration. - Collaborate with cross-functional teams to translate business requirements into effective machine learning solutions and model frameworks.