FPT Software Việt Nam đang tuyển Mid/Senior/SA – AI Engineer (LLM/Gen AI) (Banking/Insurance/Finance) 🔥

FPT Software Việt Nam đang tuyển Middle/Senior/SA – AI Engineer (LLM/Gen AI) (Banking/Insurance/Finance)

• Languages: Tiếng Anh giao tiếp khá (có thêm tiếng Nhật/Trung/Hàn/Pháp/Đức là điểm cộng)
• Contact: [email protected] (033 305 8156 - Zalo)

(*) XEM THÊM NHIỀU CƠ HỘI JOB UPDATE DAILY TẠI LINK:

https://natural-keyboard-025.notion.site/OPENING-JOB-BOARD-VER-2026-327a2daec0b080fabee6c9e84f2a3c3d?source=copy_link

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Bên dưới là JD chi tiết cho 2 levels: Junior/Middle và Senior. Anh chị có thể apply ngay hoặc ping em để hỏi thêm nhé.

(I) Đối với ứng viên Junior/Middle | 7slots

( *MUST có bằng Thạc sỹ ngành AI/Data + tiếng nhật N2 UP or tiếng Anh chứng chỉ IELTS 6.5)

(*) Job Description:

‣ Research and Development Support

– Assist in the design, development, and evaluation of AI/ML models for specific use cases.

– Conduct literature reviews and stay informed about recent advancements in AI and deep learning.

– Participate in experiments related to LLMs, prompt engineering, RAG (Retrieval-Augmented Generation), and data-driven AI pipelines.

‣ Data Preparation and Processing

– Support data collection, labeling, and cleaning for model training and evaluation.

– Work with structured and unstructured datasets, ensuring quality and consistency.

– Implement basic feature engineering and data preprocessing using Python libraries.

‣ Model Training and Testing

– Implement and test models using frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.

– Evaluate model performance and suggest improvements based on results.

– Participate in debugging and optimization of AI models for better accuracy and efficiency.

‣ Integration and Deployment Support

– Assist in integrating models into prototype applications or APIs.

– Collaborate with DevOps and engineering teams to understand model deployment workflows.

– Learn about cloud-based AI services (AWS SageMaker, Azure ML, or GCP Vertex AI).

‣ Documentation and Collaboration

– Maintain detailed documentation of experiments, datasets, and code.

– Participate in team meetings, code reviews, and research discussions.

– Contribute to project reports, technical documentation, and knowledge sharing.

(*) Job Requirements:

‣ Education: Pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline. (MUST)

‣ Technical Skills:

– Proficiency in Python and familiarity with libraries such as NumPy, Pandas, scikit-learn, and Matplotlib.

– Basic understanding of machine learning algorithms and deep learning architectures.

– Exposure to frameworks such as TensorFlow, PyTorch, or Keras.

– Familiarity with LLMs, transformers, or NLP concepts is an advantage.

– Understanding of data handling, version control (Git), and basic API usage.

‣ Soft Skills:

– Strong analytical and problem-solving mindset.

– Curiosity and willingness to learn emerging AI technologies.

– Effective communication and teamwork abilities.

– Attention to detail and commitment to high-quality work.

• Good communication ENG/JP N2+

(*) Preferred Qualifications:

‣ Experience with Hugging Face, LangChain, or OpenAI API.

‣ Familiarity with Jupyter Notebooks and Google Colab for experimentation.

‣ Participation in AI/ML projects, hackathons, or research publications.

‣ Basic knowledge of SQL or NoSQL databases.

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(II) Đối với ứng viên Senior: Có 2 JDs

JOB No.(1):

‣ Key Responsibilities

– LLM Engineering: Design, fine-tune, and optimize models such as GPT, Claude, Gemini, LLaMA, or Falcon for domain-specific use cases.

– RAG Systems: Build and maintain retrieval-augmented generation pipelines using vector databases (FAISS, Pinecone, Weaviate, etc.).

– Prompt Optimization: Develop prompt templates, chains, and agents using frameworks like LangChain or LlamaIndex.

– Model Deployment: Implement, monitor, and scale model inference endpoints using tools like MLflow, Docker, and Kubernetes.

– Performance Optimization: Evaluate models for accuracy, latency, and cost efficiency; continuously improve performance.

– Collaboration & Mentoring: Mentor junior engineers, review code, and guide best practices in AI software engineering.

– Research & Innovation: Stay updated with advancements in LLMs, multimodal AI, and open-source ecosystems; lead PoCs and innovation initiatives.

‣ Required Qualifications

– Education: Bachelor’s or Master’s in Computer Science, Artificial Intelligence, or related field (PhD preferred).

– Experience:

– 3+ years of experience in machine learning / NLP.

– 1+ years working directly with LLMs or GenAI applications.

– Technical Skills:

– Proficiency in Python and ML libraries (PyTorch, TensorFlow, Hugging Face Transformers).

– Experience with LangChain, LlamaIndex, or OpenAI SDKs.

– Strong understanding of embeddings, tokenization, and vector search.

– Familiarity with MLOps, CI/CD, and cloud environments (AWS, Azure, GCP).

– Experience integrating AI APIs (OpenAI, Anthropic, Cohere, Google Gemini).

– Soft Skills: Strong problem-solving and communication abilities; comfortable leading projects and mentoring team members.

‣ Preferred Qualifications

– Experience with model distillation and fine-tuning open-source LLMs.

– Exposure to multimodal AI (text + image + voice) applications.

– Familiarity with AI safety, bias, and governance frameworks.

____JOB No.(2)_______________________

(*) Responsibilities:

‣ Architect and implement agent workflows utilizing frameworks such as LangChain, LangGraph, or the OpenAI Agents SDK.

‣ Design multi-agent systems, utilizing tools/model-context-protocol (MCP).

‣ Develop high-performance RESTful and streaming APIs using FastAPI.

‣ Design, build, and evaluate RAG pipelines leveraging enterprise-grade vector databases.

‣ Deliver multimodal LLM features integrating text, vision, speech, and structured data.

‣ Instrument and monitor key metrics, including latency, cost, and hallucination rates.

‣ Apply core machine learning, deep learning, and Transformer-based algorithms to optimize and troubleshoot models.

‣ Design relational database schemas, write optimized SQL, and integrate transactional data sources.

Requirements:

‣ Bachelor’s degree in Computer Science, Data Engineering, or a related field.

‣ Minimum of 3 years’ experience building and operating ML/AI systems in production environments.

‣ Hands-on experience with at least one agent framework (e.g., LangChain, LangGraph, OpenAI Agents).

‣ Proven track record in delivering RAG solutions, including indexing, retrieval optimization, and evaluation.

‣ Proficiency in Python and experience with FastAPI.

‣ Familiarity with multi-agent systems with tools/model-context-protocol (MCP).

‣ Demonstrated experience with multimodal LLM projects.

‣ Strong foundation in machine learning fundamentals, deep learning architectures, and Transformer internals.

‣ Expertise in relational database design and advanced SQL.

‣ Effective communication skills in English (B2 level or higher).