Saad Muzammil
Platform EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Platform Engineer with 6+ years in Incident Management & Automation
A results-driven professional specializing in incident management, process automation, and strategic project management. I have a proven track record of developing and implementing robust automation workflows, leveraging tools like Terraform to enhance operational efficiency, reduce costs, and ensure superior system reliability. I have successfully led complex technical projects, including a critical migration that resulted in substantial annual cost savings. I am adept at training machine learning and deep learning models to derive actionable insights, which I use to optimize organizational performance and strategic decision-making. My expertise extends to maintaining an exceptionally high organization-wide SLO, ensuring high availability and seamless operations. I can take complete ownership of a project, from ideation to successful launch, while implementing best practices in the field.
Lahore University of Management Sciences
Masters of Science · Artificial Intelligence
August 1, 2026 – Present
University of Punjab, Lahore
Bachelors of Science · Operational Research
August 1, 2021 – June 30, 2021
Motive
Data Analyst
October 1, 2021 – Present
India
Motive
Platform Al Engineer
October 1, 2021 – Present
India
Vortex Solutions Inc
Technical Support Analyst
January 1, 2021 – November 1, 2021
Lahore, Punjab, Pakistan
Cappersoft
Data Analyst
January 1, 2020 – January 1, 2021
Lahore, Punjab, Pakistan
Cappersoft
Senior Data Analyst
January 1, 2020 – January 1, 2021
Lahore, Punjab, Pakistan
Large Language Model (LLM) Development
June 24, 2026 – Present
Developed a Large Language Model (LLM) for robust response generation. Used a SmolLM from Hugging Face and applied advanced fine-tuning techniques like LoRA (Low Rank Adaption) and DPO (Direct Performance Optimization) to efficiently train the model, ensuring it provided accurate and high-quality responses.
Computer Vision for Security
June 24, 2026 – Present
Developed an automated system capable of detecting faces in real-time video or image streams and then applying obfuscation to protect identities. To achieve this, I used OpenCV's pre-trained classifiers, specifically a Haar Cascade, and NumPy for efficient data manipulation. The final output was a system capable of real-time identity protection for live security feeds.
Image Similarity Search Engine
June 24, 2026 – Present
Developed a computer vision project to find the top 5 most similar images from a dataset, functioning as an image search and recommendation system. My solution involved training a model to generate embeddings from images, which were then compared using a similarity metric to identify matches. This approach provided a tangible business benefit by enhancing user experience and improving content discoverability. I utilized libraries such as TensorFlow, Keras, and scikit-learn to build and validate the model.
Machine Learning for Price Prediction
June 24, 2026 – Present
Built a Machine Learning (ML) model to predict automobile prices by leveraging five years of historical data. To ensure accuracy, I developed and compared multiple models—including Random Forest and XGBoost—on key metrics like MAE and RMSE. This strategic approach allowed me to select the most reliable and high-performing model for deployment, providing accurate forecasts that directly influenced business and pricing decisions.
Dynamic Resource Allocation for 5G (DRA5G)
June 24, 2026 – Present
Engineered a Dynamic Resource Allocation solution to optimize network performance. Using Confluent for real-time data streaming and Prefect for workflow orchestration, my solution intelligently adjusted network resources to improve efficiency, reliability, and user experience. This strategic approach enhanced network utilization and service quality by ensuring resources were allocated based on real-time demand.
Cultural Fit Analysis
The candidate's project diversity, ranging from LLM development to computer vision and dynamic resource allocation, indicates a broad interest in advanced technical domains. Their experience in both data analysis and platform AI engineering roles suggests adaptability and a willingness to tackle different challenges. The emphasis on cost savings, efficiency, and strategic project management aligns with a results-oriented culture. The candidate's current pursuit of a Master's in AI also shows a commitment to continuous learning and growth.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through root cause analysis and technical issue resolution. Their experience in mentoring junior analysts and leading projects indicates leadership potential and a collaborative mindset. The ability to automate routine tasks and improve operational efficiency aligns well with the operational aspects of a Platform Engineer role. The candidate's focus on achieving high SLOs and ensuring system reliability also points to a strong operational fit.