Amr (Ibrahim) Amer-Machine Learning Engineer
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Experience
Machine Learning Engineer
German Research Center for Artificial Intelligence (DFKI)
- Developed end-to-end reproducible ML pipelines (PyTorch) with data versioning (DVC), experiment tracking (MLflow), automated testing (PyTest), and CI/CD across all training workflows.
- Scaled Vision Transformer and CNN training across NVIDIA A100 GPU clusters (CUDA, DDP, SLURM); applied hyperparameter optimization (W&B Sweeps) to reduce training overhead and identify optimal configurations.
- Developed a real-time 3D human motion generation system (ViT, VQ-VAE, SMPL-X/PIXIE) for personality-conditioned avatar synthesis; achieved state-of-the-art FID = 6.15 and P-FID = 10.31 on the UDIVA benchmark.
- Validated model expressiveness through structured user studies, achieving 86% accuracy in distinguishing extroverted vs. introverted avatar behaviors.
- Optimized inference pipelines by deploying PyTorch models via TensorRT and ONNX Runtime into native C++ code; benchmarked performance.
Software Developer (Backend & Data Systems)
General Authority of Civil Aviation (GACA)
- Developed secure backend web services using Java and scaled enterprise data integrations across high-volume aviation systems using Oracle SOA Suite.
- Optimized relational database schemas and authored PL/SQL stored procedures to accelerate data throughput for large-scale operational workloads.
- Refactored legacy code into modular, object-oriented architectures to improve system maintainability.
Software Engineering Intern
Ejada Systems
- Developed and tested enterprise J2EE software components to support scalable backend applications.
- Built and optimized SQL queries and database modules to ensure efficient data access.
Industry Experience
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Experienced in Education, Professional Services, Aerospace and Defense, Government and Administration, and Information Technology.
Business Area Experience
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Experienced in Information Technology and Research and Development.
Summary
Machine Learning Engineer specializing in Computer Vision and Deep Learning, with an M.Sc. in Visual Computing from Saarland University. Proven track record delivering production-ready ML systems from distributed GPU training and multimodal generative models to high-performance C++ inference and end-to-end deployment.
Skills
Programming Languages
- Python
- Java
- C++ (14/17/20/23)
- Cuda
- Sql
- Bash
C++ Core Language
- Oop (Inheritance, Polymorphism, Encapsulation)
- Raii & Smart Pointers (Unique Ptr, Shared Ptr, Weak Ptr)
- Move Semantics & Perfect Forwarding
- Templates & Generic Programming
- Stl (Algorithms, Iterators, Map, Set, Unordered Map, Priority Queue)
- Concurrency (Std::Thread, Mutex, Std::Async)
- Modern C++ (Lambdas, Constexpr, Auto, Range-Based Loops)
Machine Learning
- Pytorch
- Tensorflow
- Scikit-Learn
- Monai (Medical Imaging)
- Hugging Face Transformers
- Fastai
Computer Vision
- Opencv
- Yolo (V8/V10)
- Detr
- Sam
- Bytetrack
- Deepsort
- Tracknet
- Homography & Camera Calibration
- Instance & Semantic Segmentation
- 3d Human Mesh Recovery
- Smpl-X
- Pixie
Deep Learning/Ml Architectures
- Cnns (Resnet, Efficientnet, Vgg)
- U-Net
- Gans (Conditional, Cyclegan)
- Diffusion Models
- Vision Transformers (Vit, Swin, Deit)
- Autoencoders (Vae, Vq-Vae)
- Detection Transformers (Detr, Rt-Detr)
Mlops & Experimentation
- Mlflow
- Weights & Biases
- Tensorboard
- Optuna
- Experiment Tracking
- Model Versioning
- Reproducible Pipelines
Deployment & Infrastructure
- Docker
- Kubernetes
- Fastapi
- Onnx Runtime
- Tensorrt
- Aws (Ec2, S3, Ecr)
- Multi-Gpu Training (Ddp)
- Slurm
Software Engineering
- Git
- Github
- Ci/Cd
- Scrum
- Rest Apis
- Pytest
- Performance Profiling
- Linux
Languages
Education
Saarland University
Master of Science · Visual Computing · Saarbrücken, Germany · 1.9
Arab Academy for Science and Technology
Bachelor of Engineering · Computer Engineering · Egypt · 3.2/4.0
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Experience
Global Experience
Expertise
Qualifications
Profile
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