AI Systems Developer

3 days ago

Singapore beBeeArtificialintelligence Full time

Job Title: AI / Machine Learning Engineer

We're a dynamic startup with established clients and a portfolio of contracts, specializing in the delivery of Agentic AI systems across diverse sectors including transportation, marketing, and academia.

  • Agentic AI Development:
    • Design, develop, and implement sophisticated AI agents and bots capable of independent operation, complex decision-making, and self-correction within various domain-specific contexts.
    • Utilize and seamlessly integrate with advanced AI orchestration frameworks such as LangChain and LangGraph to build robust conversational and task-oriented agents.
    • Work with state-of-the-art large language model (LLM) serving solutions like Ollama and vLLM to ensure efficient and scalable inference for our AI agents.
    • Implement Retrieval-Augmented Generation (RAG) systems to enable agents to access, synthesize, and generate responses based on external, up-to-date knowledge bases, mitigating hallucinations and ensuring factual accuracy.
    • Develop and integrate Memory, Reasoning, and Planning (MRP) capabilities within agents, allowing them to maintain context, reason over information, formulate multi-step plans, and adapt to dynamic environments.
    • Design and implement Agent-to-Agent (A2A) communication protocols, enabling seamless and secure collaboration, task delegation, and information exchange between different autonomous agents, regardless of their underlying frameworks or platforms.
  • Deployment and MLOps:
    • Strategically deploy and manage AI agents and systems on leading cloud environments, ensuring high availability, scalability, and security.
    • Expose AI functionalities through well-documented and performant APIs, enabling seamless integration with client systems and applications.
    • Handle on-premise deployments, which includes the end-to-end setup, configuration, and maintenance of Kubernetes clusters for containerized applications.
    • Implement robust containerization strategies and establish efficient orchestration workflows using tools like Argo to automate deployment, scaling, and management of AI services.
    • Establish and maintain CI/CD pipelines for AI models and applications, ensuring rapid iteration and reliable delivery.
  • Model Training & Fine-tuning:
    • Leverage expertise in deep learning frameworks to train, fine-tune, and optimize custom AI models across various data types.
    • Conduct experimentation, hyperparameter tuning, and model evaluation to achieve optimal model performance.
    • Stay abreast of the latest research and advancements in AI/ML to continuously improve our systems.

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