Skill diminta
AWSAzureDockerFastAPIFlaskGCPGitPyTorchPythonSQLScikit-learnTensorFlow
Gaji pasar untuk posisi ini
Median Rp8,3 jt/bulan · rentang umum Rp6,7 jt – Rp9,8 jt
Berdasarkan 47 lowongan Machine Learning se-Indonesia (semua level).
Lihat data gaji selengkapnya →Deskripsi
About the role
An AI Engineer role focused on designing, developing, and implementing AI-powered solutions using Python, Large Language Models, Machine Learning, Computer Vision, and Natural Language Processing technologies.
- Key responsibilities
- Design, develop, and implement AI-powered solutions using Python, LLM, Machine Learning, Computer Vision, and NLP technologies
- Build, train, evaluate, and optimize Machine Learning and Deep Learning models based on business requirements
- Develop and integrate LLM-based applications, including AI chatbots, intelligent assistants, and RAG-based systems
- Implement Computer Vision solutions for image recognition, object detection, OCR, and visual data analysis
- Develop NLP solutions for text processing, classification, information extraction, and semantic understanding
- Build scalable APIs and integrate AI models into existing enterprise applications
- Perform model evaluation, performance optimization, debugging, and continuous improvement
- Collaborate with software engineers, data engineers, and business stakeholders to deliver production-ready AI solutions
- Maintain technical documentation and follow best practices in AI development and deployment
- About you
- Bachelor's degree (S1) in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related fields
- Minimum 3 years of professional experience as an AI Engineer, Machine Learning Engineer, or related role
- Strong proficiency in Python programming, including experience developing, optimizing, and deploying AI/ML solutions
Strong knowledge and hands-on experience in Large Language Models (LLM), Machine Learning, Computer Vision, and Natural Language Processing (NLP)
- Experience working with LLM frameworks and technologies such as LangChain, Hugging Face Transformers, OpenAI API, or similar tools
- Proficient in Machine Learning and Deep Learning frameworks, including TensorFlow, PyTorch, and Scikit-learn
Hands-on experience in Computer Vision, including image processing, object detection, image classification, and OCR using OpenCV, YOLO, or similar frameworks
Strong understanding of NLP techniques, including text classification, sentiment analysis, named entity recognition (NER), embeddings, and semantic search
- Experience developing and integrating AI models through REST APIs using FastAPI or Flask
- Familiarity with SQL/NoSQL databases, Git, Docker, and cloud platforms (AWS, Azure, or GCP)