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Check with seller Kỹ sư ứng dụng Trí tuệ nhân tạo (AI Engineer)
- Location: Hà Nội, vietnam
Role Overview
We are seeking a highly skilled and inventive AI Engineer to join our development team. In this role, you will be responsible for building, integrating, and deploying artificial intelligence and machine learning models into real-world applications. Whether you are fine-tuning Large Language Models (LLMs), implementing computer vision solutions, or designing intelligent automation workflows, your work will be essential to making our products smarter and more responsive to user needs. We offer a fast-paced environment where you will work with cutting-edge MLOps pipelines and state-of-the-art AI frameworks. If you are passionate about bridging the gap between AI research and scalable software products, possess strong programming capabilities, and enjoy tackling challenging, non-deterministic problems, this is an excellent opportunity to build the next generation of intelligent systems.
Key Responsibilities
AI Model Development: Design, train, and fine-tune machine learning models (including LLMs, generative models, or predictive models) to solve specific business problems.
Production Deployment: Implement scalable APIs and services to integrate AI models into web or mobile applications, ensuring high availability and low latency.
MLOps & Automation: Build and manage automated pipelines for data ingestion, model training, evaluation, and deployment to ensure consistent and reproducible results.
Performance Tuning: Monitor model performance in production, implement feedback loops for continuous learning, and optimize models for inference speed and cost-efficiency.
Data Pipeline Engineering: Collaborate with data teams to clean, augment, and structure large datasets for model training and validation.
Research & Implementation: Stay current with the rapidly evolving AI landscape (e.g., new paper architectures, pre-trained model APIs, or vector databases) and apply these advancements to improve product features.
Cross-Functional Collaboration: Partner with software engineers, product managers, and designers to identify opportunities for AI integration and ensure smooth project delivery.
Requirements & Qualifications
Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
Experience: Proven experience in building and deploying machine learning applications. A strong portfolio or GitHub repository showcasing your AI projects is highly preferred.
Technical Skills:
Programming: Mastery of Python and its AI/ML ecosystem (e.g., PyTorch, TensorFlow, Scikit-learn, LangChain).
Cloud & Infrastructure: Experience with cloud AI platforms (AWS SageMaker, Google Vertex AI, or Azure AI) and containerization (Docker, Kubernetes).
Modern AI Stack: Familiarity with vector databases (e.g., Pinecone, Milvus), API integration (OpenAI, Anthropic, or Hugging Face), and RAG (Retrieval-Augmented Generation) architectures.
Software Engineering: Proficiency in Git, CI/CD pipelines, and writing production-ready, clean, and documented code.
Personal Attributes:
Problem-Solving: An ability to navigate the ambiguity of AI development, where solutions often require iterative experimentation.
Adaptability: A continuous learner who can quickly adapt to new research breakthroughs and evolving toolsets.
Systemic Thinking: Understanding how to balance model performance with system constraints like compute costs and latency.
Collaboration: A proactive team player who can clearly communicate technical limitations and possibilities to non-technical stakeholders.
Tags: AI Engineer, Machine Learning Engineer, Generative AI, MLOps, LLM Integration, RAG, Software Engineer, Artificial Intelligence, Data Engineering, Automation.
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