• Collaborating with data scientists and domain experts to understand project requirements and formulate machinelearning objectives.• Collecting, preprocessing, and cleaning large datasets to ensure data quality and integrity.• Performing exploratory data analysis (EDA) to gain insights and identify relevant features for model development.• Engineering and selecting appropriate features, transforming raw data into suitable input for machine learningalgorithms.• Develop, train, and validate machine learning models using algorithms such as decision trees, random forests,support vector machines (SVM), neural networks, deep learning architectures etc.• Optimizing models for performance, accuracy, and efficiency by fine-tuning hyperparameters and applying regularization techniques.• Evaluate model performance using appropriate metrics such as accuracy, precision, recall, F1-score, or area underthe curve (AUC).• Monitor and maintaining deployed models, addressing issues such as concept drift, data drift, or modeldegradation.• Collaborate with software engineers to implement APIs, interfaces, or user-friendly applications for accessing andutilizing machine learning models.• Stay up-to-date with the latest research, techniques, and trends in machine learning and AI by reading papers,attending conferences, or participating in online communities.• Utilize Reinforcement Learning with Human Feedback (RLHF) to iteratively improve the quality and coherence ofgenerated content based on human evaluation

• Design and developing server-side applications, APIs, and web services.• Implementing business logic and algorithms to handle data processing, calculations, and database operations.• Implementing serverless functions and serverless applications using Cloudflare Workers.• Worked with databases (e.g., SQL or NoSQL) to store, retrieve, and manipulate data efficiently.• Ensure data security and implement authentication and authorization mechanisms to control access to sensitiveinformation.• Optimizing server-side code for performance, scalability, and efficiency.• Collaborating with frontend developers to define and implement APIs that meet the requirements of the user interface.• Integrating with external services and APIs to fetch data or perform specific actions.• Implementing caching mechanisms to improve application performance and reduce load on the server.• Writing unit tests and conduct integration testing to ensure code quality and maintainability.• Monitoring and analyzing server performance, identifying and resolving bottlenecks or issues.• Debugging and troubleshooting production issues, ensuring smooth operation of backend systems.• Implementing logging and monitoring systems to track application behavior and performance.• Ensure compliance with relevant coding standards, security guidelines, and best practices.• Collaborate with cross-functional teams, including frontend developers, data scientists, and DevOps engineers, todeliver comprehensive solutions.• Maintaining and updating existing backend systems, addressing bugs, implementing new features, or improvingperformance.• Documenting code, system architecture, and technical specifications for future reference.

• Designed and developed both server-based and serverless APIs, optimizing performance and scalability acrossvarious environments.• Expertly crafted RESTful services, ensuring seamless integration with front-end applications and third-partysystems, adhering to best practices for API design.• Proficient in working with both SQL and NoSQL databases, including schema design, query optimization, and data migration. Implemented efficient data storage and retrieval strategies to enhance application performance.• Developed and maintained robust backend systems using Node.js and NestJS, implementing advanced featuressuch as middlewares, guards, and filters to enhance application security and functionality.• Implemented comprehensive authorization and authentication mechanisms, utilizing industry-standard protocols(e.g., OAuth, JWT) to secure user access and protect sensitive data.• Applied security best practices in API development, including rate limiting, data validation, and encryption, tosafeguard against common vulnerabilities.• Developed custom middlewares to handle tasks such as logging, error handling, and request validation, improvingthe overall efficiency and maintainability of applications.• Designed scalable backend architectures that can efficiently handle growing traffic and data, leveraging both traditional and modern infrastructure setups.• Integrated CI/CD pipelines to automate testing, deployment, and monitoring processes, ensuring rapid delivery ofhigh-quality software updates.

Machine Learning & Deep Learning Engineer• Developed and deployed machine learning models using Python libraries like TensorFlow, Keras, and Scikit-learn.• Worked on data preprocessing, feature engineering, and model selection for various supervised and unsupervisedlearning tasks.• Fine-tuned pre-trained deep learning models for specific use cases, including image recognition and natural language processing.• Implemented model evaluation and validation techniques to ensure high accuracy and generalization.• Integrated machine learning models into production systems, ensuring scalability and reliability.

Backend Engineer (Node.js, Python, PHP)• Designed and implemented RESTful APIs and microservices using Node.js, Python (Django/Flask), and PHP.• Developed and maintained scalable backend systems, handling complex data processing tasks and ensuringefficient database interactions.• Integrated third-party services and APIs, ensuring seamless data exchange and authentication processes.• Implemented middleware, guards, and filters for enhanced security and performance optimization.• Worked with both SQL and NoSQL databases, optimizing queries and database structures for performance.• Collaborated with front-end developers to design and deliver end-to-end solutions for web applications.