03/11/2026 updated
100 % available
AI Engineer & Machine Learning Engineer
Dhaka, Bangladesh
Only remote
B.Sc. in Data Science & EngineeringAbout me
AI and Machine Learning Engineer experienced in building and deploying production ML and LLM systems. Skilled in FastAPI Docker and scalable architectures with focus on reliability real time inference monitoring and model evaluation. Strong Data Science and Engineering background CGPA 3.54/4.00.
C (Programming Language)Java (Programming Language)Application Programming Interfaces (APIs)Artificial IntelligenceComputer VisionC++ (Programming Language)DevOpsGitHubImage ProcessingPython (Programming Language)PostgreSQLMachine LearningMongoDBOpenCVTelemetry
Machine Learning & Deep Learning
Expertise in PyTorch, TensorFlow, Scikit-learn, and ONNX Runtime for building and deploying ML models with focus on LLM systems and multi-agent orchestration
Production-Grade AI Systems
Experience in designing, deploying, and operating production-grade ML and LLM systems with observable, testable, and reproducible AI services using FastAPI, Docker, and Kubernetes-ready architectures
Backend Development & APIs
Proficiency in FastAPI, REST APIs, and Async Systems for building scalable backend solutions with real-time inference capabilities
Programming Languages
Strong foundation in Python, C++, Java, and C for developing diverse software solutions
Database Management
Experience with PostgreSQL, MongoDB, SQLite, Vector DBs including FAISS, Pinecone, and Chroma for data storage and retrieval
DevOps & Containerization
Proficiency in Docker, Kubernetes, Git, GitHub, and Hugging Face for deployment and version control
Computer Vision
Expertise in OpenCV, ORB, SSIM for image processing and change detection systems
MLOps & Monitoring
Experience with Prometheus, OpenTelemetry, Structured Logging, and Model Versioning for production ML systems
LLM Technologies
Advanced knowledge in LangChain, LangGraph, RAG, Prompt Engineering, and Multi-Agent Systems
Expertise in PyTorch, TensorFlow, Scikit-learn, and ONNX Runtime for building and deploying ML models with focus on LLM systems and multi-agent orchestration
Production-Grade AI Systems
Experience in designing, deploying, and operating production-grade ML and LLM systems with observable, testable, and reproducible AI services using FastAPI, Docker, and Kubernetes-ready architectures
Backend Development & APIs
Proficiency in FastAPI, REST APIs, and Async Systems for building scalable backend solutions with real-time inference capabilities
Programming Languages
Strong foundation in Python, C++, Java, and C for developing diverse software solutions
Database Management
Experience with PostgreSQL, MongoDB, SQLite, Vector DBs including FAISS, Pinecone, and Chroma for data storage and retrieval
DevOps & Containerization
Proficiency in Docker, Kubernetes, Git, GitHub, and Hugging Face for deployment and version control
Computer Vision
Expertise in OpenCV, ORB, SSIM for image processing and change detection systems
MLOps & Monitoring
Experience with Prometheus, OpenTelemetry, Structured Logging, and Model Versioning for production ML systems
LLM Technologies
Advanced knowledge in LangChain, LangGraph, RAG, Prompt Engineering, and Multi-Agent Systems
Languages
EnglishFluent
Project history
Built a production-grade LLM observability platform with prompt versioning, risk controls, and multi-model fallback. Designed automated LLM evaluation pipelines using ensemble LLM-as-judge scoring for quality, safety, and hallucination detection.
Developed a low-latency ML inference API supporting multi-model and multi-version serving. Achieved sub-100ms inference latency with ONNX Runtime and Redis-backed intelligent caching.
Built a multi-agent LLM system for querying medical datasets using natural language. Implemented NL-to-SQL pipelines with automated routing between database tools and medical web search agents.