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AI Ops Engineer (Team Lead)

AI Ops Engineer (Team Lead)

TG HUMAN RESOURCE MANAGEMENT SERVICES SDN BHDKuala Lumpur, Kuala Lumpur, Malaysia
6 hari lalu
Penerangan pekerjaan

We are seeking a passionate and driven AI Engineer with strong Python skills & Generative AI (GenAI) to join our team. This role offers the opportunity to work on end-to-end AI / ML projects involving web APIs, automation, NLP, image and object recognition, and cutting-edge GenAI applications. You’ll be part of a collaborative team focused on delivering innovative, scalable AI solutions.

  • Develop automation scripts to streamline workflows and processes.
  • Design and implement web APIs and basic user interfaces for AI applications.
  • Build web scrapers for data extraction from public sources.
  • Research and evaluate state-of-the-art (SOTA) ML / GenAI literature and integrate findings into practical solutions.
  • Design and build AI / ML models
  • Build Image classification and object recognition
  • Build NLP tasks (e.g., sentiment analysis, text summarization, LLM fine-tuning)
  • Build Generative AI tasks such as text generation, embeddings, or prompt engineering
  • Convert trained models into scalable APIs or services.
  • Conduct data analysis, interpret results, and derive actionable insights.
  • Support model deployment, monitoring, and performance optimization.

Job Requirements

  • Minimum at Bachelor’s in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Minimum 2 years of experience related
  • Experience in Deep Learning libraries (e.g., TensorFlow, PyTorch, Transformers, Keras)
  • Experience in NLP and vision tasks
  • Experience in Version control using Git
  • Experience in RESTful API integration
  • Strong Python programming foundation with a focus on clean, efficient code.
  • Eagerness to explore and implement ML, deep learning, and GenAI models.
  • Familiarity with model lifecycle from training to deployment
  • Familiarity with Generative AI functions, tools and frameworks (e.g., OpenAI, Hugging Face Transformers, LangChain, RAG)

    • Good To Have

  • Experience with MLOps tools or platforms (e.g., Dataiku, MLflow, FastAPI).
  • Understanding of learning paradigms : supervised, unsupervised, reinforcement learning.
  • Familiarity with containerization tools (Docker, Podman) and cloud environments.
  • Basic knowledge of UI / UX or front-end integration for AI tools.

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    Ai Engineer • Kuala Lumpur, Kuala Lumpur, Malaysia