Senior AI/ML Engineer-NLP, CV, Gen AI, MLOps

Ahsen Mahmood

Senior AI/ML Engineer NLP Computer Vision Generative AI Predictive

Modeling Deep Learning MLOps AWS SageMaker Time Series Analysis LLMs RAG Docker Kubernetes

************.****@*****.*** +1-612-***-****

Parsippany, New Jersey 07054, United States

PROFILE

AI/ML engineer with 8+ years of experience building end-to-end intelligent systems in NLP, computer vision, generative Al, and predictive analytics, backed by a strong foundation in data science and a CS degree from COMSATS University. Expert in scalable ML pipelines and MLOps using Python, PyTorch, TensorFlow, and scikit- learn, delivering impactful solutions like tions like Al chatbots, RAG-based systems, and automated decision- making tools. Skilled in developing predictive models, computer vision applications, and transforming complex datasets into actionable insights that solve real-world challenges at scale. PROFESSIONAL EXPERIENCE

AI/ML Engineer, Expert Systems Solutions

•Led the development of speaker recognition systems, including enrolment pipelines linked to user databases, leveraging cutting-edge open-source models for high-accuracy identification.

•Specialized in designing, training, and deploying high-performance Al models for enterprise applications in NLP and computer vision, leveraging deep learning frameworks such as PyTorch and TensorFlow.

12/2020 – Present

Texas, United States

•Optimized Al models for efficient execution on specialized hardware, including SambaNova's custom Al accelerators, focusing on scalability, real-time inference, and performance tuning across large datasets.

•Integrated machine learning algorithms into complex workflows to enhance product development and system performance, applying supervised learning and neural networks.

•Developed advanced solutions for real-time inference and model optimization, ensuring low latency and high throughput in production environments.

•Applied NLP techniques to extract actionable insights from unstructured data, oporting intelligent automation and decision-making in enterprise systems.

•Established data-driven engineering practices using Python visualization tools to communicate performance metrics and guide strategic optimizations.

•Leveraged graph and network analysis, A/B testing, and statistical analysis to uncover operational patterns, improve decision-making, and validate ML-driven insights.

Machine Learning Engineer, Bahaii Consulting

•Worked as a Machine Learning Engineer at Bahaji Consulting for 3 years, developing and deploying Al models for creative applications. as video generation, image editing, and text-to-image tools.

•Trained deep learning models using Python and PyTorch, applying advanced techniques like hyperparameter tuning and model validation to optimize lability 02/2018 – 10/2020

New York, United States

performance and reliab

•Optimized models for real-time responsiveness and integrated them with cloud- based systems using platforms like AWS and Docker to ensure scalable and user- friendly creative tools.

•Engineered Al solutions leveraging computer vision and deep learning frameworks to automate content generation and editing workflows, improving user experience and efficiency.

•Conducted applied research focused on deploying robust AI models in production environments, ensuring scalability, low latency, and high availability.

•Applied NLP techniques to enhance text-to-image and creative content generation tools, enabling more accurate and context-aware outputs.

•Collaborated with cross-functional teams to desi to design and implement MLOps pipelines, streamlining model deployment and monitoring processes.

•Established data-informed decision-making practices within engineering firms, utilizing Python-based visualization tools (e.g., Matplotlib, Seaborn) to communicate insights and guide strategic planning

EDUCATION

Masters in Computer Science, COMSATS University 01/2013 – 11/2016 SKILLS

Core Machine Learning & Al

•Supervised & Unsupervised Learning

•Deep Learning

•Natural Language Processing (NLP)

•Computer Vision

•Generative Al

•Predictive Model Development

•Reinforcement Learning

•Transfer Learning

•Time Series Analysis

•Anomaly Detection

•Model Optimization & Hyperparameter Tuning

•Feature Engineering & Data Preprocessing

Soft Skills

•Problem Solving & Critical Thinking

•Collaboration with Cross-Functional Teams

•Strong Communication & Documentation

•Adaptability & Continuous Learning

•Time Management & Prioritization

•Attention to Detail

•Analytical Thinking

•Creativity & Innovation

•Leadership & Mentorship

MLOps & Deployment

•Model Deployment (Flask, FasLAPI)

•Docker & Kubernetes

•RESTful APIs for Al services

•ML Pipelines & Automation

Tools & Platforms

•Azure ML

•AWS SageMaker

•GCP Vertex Al

•MLflow

•Weights & Biases (W&B)

•Kubeflow Pipelines

•Apache Airflow

•Kubernetes

Data Engineering & Programming & Frameworks

•Handling

•Dala Preprocessing & Cleaning

•Feature Engineering

•SQL, NoSQL, BigQuery

•Data Versioning (DVC)

•Python (NumPy, Pandas)

•PyTorch, TensorFlow, Keras

•OpenCV, Hugging Face

•Transformers

•Jupyter, Colab

PROJECTS

Al-Powered Chatbot with RAG and LangChain, Built a conversational Al system using Retrieval-Augmented Generation (RAG), integrating LangChain, vector databases, and Hugging Face models for context-aware responses.

Sentiment Analysis with NLP, Developed a sentiment classification model using Python, NLTK, and Scikit-learn to analyze product reviews and social media data, achieving over 90% accuracy. Object Detection with YOLOVS, Implemented real time object detection using YOLOVS and OpenCV to recognize and track multiple classes in video strea Deployed using Flask for browser access. Al Resume Screening Tool, Built an ML model to parse and rank resumes using NLP and cosine similarity. Automated job matching by comparing resumes with job descriptions. ML Model Deployment on AWS SageMaker, Deployed a deep learning model using AWS SageMaker for real time predictions. Included model versioning, endpoint setup, and CI/CD integration. Predictive Maintenance System, Developed a predictive maintenance model using LSTM for time series forecasting and anomaly detection. Tracked experiments with MLflow and deployed on AWS SageMaker, reducing downtime by 30%.

Image-to-Image Translation using GANS, Developed a Pixa Pix model for turning sketches into realistic images. Trained on a custom dataset and used Weights & Biases for experiment tracking and visualization. Real-Time Object Detection System for Safety Monitoring, nitoring Built a YOLOvs-based object detection model for identifying safety gear violations on time. Integrated with GCP for scalable processing and alert systems.

n sites in real-

Forecasting Energy Consumption with Time Series Modeling, Designed and deployed an ML pipeline to forecast electricity consumption across regions using XGBoost and Prophet. Improved prediction accuracy by 20% through feature selection and hyperparameter tuning.

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