Location: Amman
Employment Type: Full-Time
Experience Required: 2-3 years
Job Summary:
We're seeking a passionate and well-rounded AI Engineer with 2-3 years of experience in applied AI and MLOps. You'll work on building, optimizing, and deploying AI systems--ranging from LLMs to computer vision and audio pipelines. This role combines research implementation, infrastructure deployment, and hands-on coding in Python.
Core Requirements:
1. AI & ML Expertise
- Solid foundation in machine learning and deep learning algorithms.
- Hands-on experience with training and fine-tuning Large Language Models (LLMs).
- Skilled in prompt engineering, retrieval-augmented generation (RAG), and LLM chaining techniques.
- Familiarity with Ollama or similar lightweight local LLM deployment frameworks.
2. Optimization & Performance
- Strong understanding of model optimization techniques (quantization, pruning, distillation, etc.).
- Experience with CPU and GPU parallelism (e.g., multiprocessing, CUDA, or joblib).
- Able to evaluate and improve inference latency, memory usage, and serving throughput.
3. Python Engineering & Deployment
- Advanced Python programming skills.
- Experience deploying Python apps for AI (FastAPI, Flask, Streamlit, Gradio).
- Familiarity with containerization and deployment using Docker and Kubernetes.
4. Cloud & DevOps
- Experience with at least one major cloud platform (AWS, GCP, or Azure)-especially for AI workloads.
- Hands-on with GPU provisioning, storage, and monitoring for production AI systems.
- Use of Terraform, CI/CD, and other infrastructure tools is a plus.
5. Hardware & Systems Knowledge
- Understanding of hardware requirements for training and serving AI models:
- NVIDIA GPU types (e.g., A100, RTX 4090) - TPU basics (if applicable)
- Importance of VRAM, CPU threading, and IOPS
- Ability to size workloads to hardware efficiently.
6. Applied Modalities
- Computer Vision: Familiarity with OpenCV, image augmentation, object detection, and segmentation.
- Audio AI: Experience with audio classification, speech-to-text (e.g., Whisper), and voice cloning/synthesis.
- Knowledge of data preprocessing pipelines for image and audio inputs.
Nice to Have:
- Familiarity with frameworks like Hugging Face Transformers, LangChain, or LlamaIndex.
- Knowledge of ONNX, TensorRT, or other model export/acceleration formats.
- Experience using Ollama with custom models or LoRA tuning.
- Exposure to real-time AI applications (streaming audio/video, inference servers, etc.).
Soft Skills:
- Ability to work in cross-functional teams.
- Clear communication--especially when discussing model trade-offs or hardware constraints.
- Curiosity-driven, with a focus on experimenting and optimizing.
Education:
- Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field.
- Relevant certifications or project portfolios are a plus
