AI Engineer
Summary
AI/ML Engineer with ~5 years of experience spanning machine learning, data engineering, and edge AI. Skilled in building RAG systems, multimodal generative AI pipelines, and large-scale ETL processing (10M+ records, 5TB+ data). Experienced in deploying optimized models on edge devices and cloud platforms (AWS/Azure), with strong MLOps, NLP, and computer vision expertise. Holds a patent in YOLO-based crowd detection and actively leads AI research and applied systems development.
Expectations
Im looking for a role where I can take real ownership of ideas, ship fast, and be accountable for outcomes. I thrive in high-energy teams that brainstorm openly, challenge each other constructively, and collaborate with trust and friendliness while continuously learning and building meaningful, user-focused products.
Employment Preferences
Expected Base Salary
**0,000 USD
Expected Total Compensation
**0,000 USD
Academic Degree
Experience
Total Professional Experience
Startup Experience
Big-Tech Companies
Enterprise Experience
Skills
- Artificial Intelligence
- Machine Learning
- Machine Learning Engineering
- Data Engineering
- Generative AI
- Large Language Models
- Small Language Models
- RAG
- Retrieval-Augmented Generation
- NLP
- Natural Language Processing
- Computer Vision
- Multimodal AI
- Stable Diffusion
- CLIP
- Whisper
- PyTorch
- TensorFlow
- Hugging Face
- Scikit-learn
- OpenCV
- Edge AI
- ONNX
- TensorRT
- CUDA
- Jetson Orin
- Embedded AI
- ESP32
- MLOps
- MLflow
- Airflow
- Spark
- PySpark
- Kafka
- ETL
- Data Pipelines
- Azure
- AWS
- Docker
- Kubernetes
- REST APIs
- GRPC
- React
- TypeScript
- Python
- SQL
- NoSQL
- Oracle SQL
- Power BI
- Pinecone
- LangChain
- CrewAI
- Prompt Engineering
- Model Optimization
- Quantization
- Mixed Precision Training
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