Senior Applied Machine Learning Engineer

2 weeks ago

Pasig, National Capital Region, Philippines Intelegencia Full time ₱120,000 - ₱180,000 per year

Intelegencia is looking for a highly skilled 
Senior Applied Learning Engineer
 to lead the development of next-generation AI systems that integrate speech, vision, and large language model (LLM) technologies. This role is ideal for innovators who thrive in designing intelligent, real-time applications that blend multiple AI disciplines into seamless, high-performance solutions.

Key Responsibilities

  • Design and optimize 
    Speech AI Pipelines
     (STT, TTS) with a focus on latency, streaming, and performance.
  • Build and deploy 
    Conversational AI systems
     using advanced LLM integration, dialogue management, and intent recognition.
  • Develop and maintain 
    low-latency real-time systems
     leveraging WebRTC, sockets, and gRPC.
  • Apply 
    Computer Vision techniques
     for object detection, video analysis, and automated decision-making workflows.
  • Architect 
    AI orchestration frameworks
     that enable collaboration between LLMs, CV models, and custom logic.
  • Manage 
    end-to-end ML deployment
    , including containerization (Docker, Kubernetes), GPU optimization, and cloud scaling.
  • Write high-quality, production-grade code in 
    Python
     (PyTorch, TensorFlow) and 

     for real-time applications.
  • Implement 
    APIs, databases, RAG pipelines
    , and multi-agent orchestration using frameworks such as Langflow, LangChain, or CrewAI—or build custom frameworks from scratch.
  • Apply 
    reinforcement learning
     strategies to optimize AI decision-making processes.
  • Contribute to internal innovation initiatives, including 
    vibe coding
     and advanced AI experimentation.

Qualifications

  • 5+ years of experience in Speech AI pipelines (STT/TTS, latency optimization, streaming).
  • 3–5+ years in Conversational AI and real-time dialogue management.
  • 5+ years in real-time systems engineering and low-latency streaming.
  • 5+ years in Computer Vision (YOLO, SAM, video analysis).
  • 5+ years in AI orchestration and hybrid workflow design.
  • 7+ years in ML deployment and cloud scaling (Docker, Kubernetes, GPU optimization).
  • 7+ years in Python/TypeScript with 2+ years in API design and framework development.
  • 1+ year in vibe coding; 5+ years in reinforcement learning.

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