Hamza Salaar-AI Engineer | Computer Vision & Multimodal Perception Systems
Check rate
Experience
Research Associate - AI & Autonomous Systems
Hochschule Coburg
- Developed and implemented AI-based perception and multimodal systems for real-world environments
- Built, trained, and evaluated Machine Learning and Deep Learning models using Python, PyTorch, TensorFlow, and OpenCV
- Worked with Vision-Language Models (VLMs), Large Language Models (LLMs), transformer-based architectures, and multimodal AI systems
- Applied LoRA-based fine-tuning techniques and experimented with diffusion models for generative and multimodal AI applications
- Developed multimodal perception pipelines using camera, LiDAR, and sensor data
- Designed end-to-end workflows for data processing, model training, evaluation, benchmarking, and robustness analysis
- Utilized HuggingFace Transformers and modern Deep Learning frameworks for AI experimentation and deployment workflows
- Applied GPU-accelerated computing, CUDA-based processing, ONNX, and TensorRT optimization for efficient inference and large-scale model training
- Collaborated with industry partners including Valeo and REHAU on applied AI and intelligent system projects
- Developed scalable AI architectures and prototype software solutions for automation and perception tasks
Research Associate - Image Processing & AI Systems
Fraunhofer Institute for Integrated Circuits IIS
- Developed Computer Vision and Image Processing algorithms for image and video analysis
- Worked on signal processing and video coding systems with focus on efficiency, robustness, and performance optimization
- Implemented Deep Learning pipelines for image enhancement, feature extraction, and multimodal data processing
- Built reproducible training and evaluation pipelines for large-scale image and sensor datasets using PyTorch and TensorFlow
- Performed algorithm benchmarking, validation, and performance analysis under real-world constraints
Industry Experience
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Experienced in Information Technology and Education.
Business Area Experience
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Experienced in Information Technology, Research and Development, and Product Development.
Summary
AI Engineer with experience in Computer Vision, Multimodal AI, Perception Systems, and Applied Machine Learning. Strong background in developing and optimizing AI systems for real-world environments using Vision-Language Models (VLMs), Large Language Models (LLMs), transformer-based architectures, and Deep Learning pipelines. Hands-on experience with LoRA fine-tuning, diffusion models, multimodal perception systems, GPU-accelerated computing, and deployment-oriented AI optimization using CUDA, ONNX, and TensorRT. Experienced in end-to-end AI workflows including data preparation, model training, evaluation, benchmarking, and scalable inference optimization.
Skills
Python, C++, Matlab
Pytorch, Tensorflow, Opencv
Numpy, Pandas, Scipy
Linux, Git, Docker
Cuda-Based Gpu Acceleration
Onnx & Tensorrt Optimization
Deployment-Oriented Ai Inference
Large-Scale Data Processing
Docker, Linux & Gpu-Based Development Environments
Computer Vision & Image Processing
Machine Learning & Deep Learning
Transformer-Based Deep Learning Models
Vision-Language Models (Vlms) & Large Language Models (Llms)
Multimodal Ai Systems
Diffusion Models & Generative Ai
Lora Fine-Tuning & Model Optimization
Object Detection & Scene Understanding
Ai Pipeline Development & Optimization
Data Preparation, Validation & Benchmarking
Languages
Education
Technische Universität Ilmenau
M.Sc. · Media Technology · Ilmenau, Germany
AIR University
B.Sc. · Electrical Engineering · Islamabad, Pakistan
Statistics
Experience
Global Experience
Expertise
Qualifications
Profile
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Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
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