REHMAN MALLAH

• AWS Certified Cloud Practitioner and CompTIA A+ Certified
• Programming proficiency in Python (Django, Flask, FastAPI), C | Working proficiency in C++, Java, Scala
• Framework and Tools: Git, Docker, MS Azure, Kubernetes, Linux, HTML+ CSS, Pytorch, LangChain, SQL

• Created Python & bash programs to automate integration testing, improving product reliability before production
• Performed local penetration tests to identify critical security threats on cloud platforms before deployment
• Optimised infrastructure management by implementing Kubernetes clusters and Docker containers, reducing deployment times greatly across AWS and Azure platforms
• Managed and setup VMs on VMware ESXi
• Enhanced software delivery processes by developing CI/CD pipelines in Azure DevOps with integrated continuous inspection tools
• Resolved technical issues for dozens of customers via Webex calls, ranging from installation to complex LDAP issues

• Developed a Python web scraping tool to automate product information collection from major supermarket websites
• Streamlined user management on AWS by creating and organizing groups and OUs, ensuring compliance with company policies and enhancing overall system security
• Monitored EC2 compute servers on AWS and troubleshooted hardware and software faults on AWS lighthouse.

• Conducted research on over a dozen AI algorithms and machine learning techniques, applying these insights to model a compiler optimisation problem to be solved using AI.
• Designed and Implemented a metaheuristic method with simulated annealing to identify optimal compiler flags for specific programs to improve their execution speed. Project was a success with a 20% performance increase
• Authored research paper, which demonstrated results comparable to the leading research in the field.

• Led six-person team in 2-month project for Wayra (Telefónica subsidiary) to develop portfolio management product
• Implemented hybrid Waterfall-Agile development model and engaged in continuous communication with the client over two months, organising meetings to gather requirements and addressing emerging issues.
• Utilised AirTable API to sync data from client database with our web application.
• Developed all database functionalities including capabilities to search, filter, add and delete records.

• Designed and implemented only the decoder transformer with sequential Neural Networks to create GPT LLM architecture.
• Tokenised input text using cl100k_base, converted it into vector embeddings, and applied a multi-head attention mechanism to generate decoder inputs for advanced sequence processing.
• Trained the neural network using a massive open-source replication of the WebText dataset from OpenAI
• Optimised model performance through hyperparameter tuning and gradient clipping methods.

• Developed a trading bot implementing statistical arbitrage strategies based on cointegration and Z-score analysis
• Integrated DYDX API for market data retrieval and order execution
• Deployed on AWS for 24/7 operation, utilising CRON for automation and Kelly Criterion for risk management