Hola, Daniel is a results-oriented Back-End & Artificial Intelligence Engineer with a Bachelor's degree in Information and Communication Engineering and 5+ years of experience designing and implementing end-to-end Machine Learning and Deep Learning pipelines. Proficient in Python, FastAPI, Django Rest Framework, .NET, and SQL, Daniel specializes in NLP and Computer Vision applications.
Expertise:
- Agent Development - LangGraph & LangChain
- Data preparation/cleansing
- Model building, AWS, Digital Ocean, MLOps
- Algorithm evaluation for Regression, Classification, Bayesian Hyperparameter optimization
- Machine Learning Lifecycle management (MLflow),
- Gradient Boosting, XGBoost, LightGBM, Random Forest, Decision Tree, KNN
- Object Detection (Vgg16, ResNet50, EfficientNetB1, MobileNet V2) and Tracking
- Pose Estimation (MoveNet, Mediapipe)
Achievements:
- Ranked 454/1181 in the Analytics Vidhya JOB-A-THON competition.
Key Skills:
- Computer Vision
- Embedded Systems
- Natural Language Processing
MLOps:
- Experiments Tracking, Logging, and Model Registry (MLflow)
LLM fine-tuning & Prompt Engineering:
- Open Source Models: Falcon, Llama-2/3, Gemini, Mistral AI
- Closed Source Models: OpenAI GPT-3/4, Anthropic Claude-Sonnet, AWS BedRock
- RAG (Retrieval Augmented Generation), Qdrant & ChromaDB Vector Database
LLM Serving Engine:
- Llama cpp
- VLLM
CI/CD:
- GitActions, Circleci
Container Orchestration Tools:
- Docker, Kubernetes
Database:
- PostgreSQL, MySQL, MongoDB, Redis, SQLAlchemy, ElasticSearch
Cloud Computing:
- AWS, Digital Ocean
Back-End & API Development:
- Django Rest Framework, FastAPI, Flask, Quart, ASP.NET MVC
Test:
- Pytest, Unittest, xUnit
API Testing Tool:
- Postman
Linux, and Version Control:
- Git
Python ML/DL packages:
- HuggingFace, AioRTC, MediaPipe, Numpy, Scikit-learn, Pandas, TensorFlow 2, Keras, OpenCV, Scrapy, Apache Spark, DeepSpeech, NLTK, Dlib, Imutils, PyAudio
GitHub:
https://github.com/danielAdama
Portfolio:
https://daniel-adama.vercel.app/
Contact:
- Email: adamadaniel321@gmail.com
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