Aizhan Azhybaeva

ML Architecture Engineer at mlai.qa

Aizhan Azhybaeva is an ML architecture engineer at mlai.qa - the specialist ML Architecture and Strategy practice for Series A-C AI startups scaling from prototype to production.

Focus

Aizhan publishes architecture-level guidance on:

  • ML platform design - end-to-end architecture from data to model serving
  • MLOps foundations - Kubeflow, Ray, MLflow, feature stores, model registries
  • Data pipeline architecture - streaming and batch ingestion, feature engineering, training-serving consistency
  • Model serving infrastructure - vLLM, Ray Serve, Triton, KServe, model routing patterns
  • RAG vs fine-tuning decisions with measured trade-offs for specific use cases
  • Build vs buy ML infrastructure - when to use managed services (OpenAI API, Bedrock, Vertex AI) vs self-hosted
  • AI stack evaluation - framework comparisons, deployment topology recommendations

Pair engagements with aiml.qa: architect with mlai.qa, validate with aiml.qa. The NomadX AI lifecycle: Design -> Validate -> Stress-Test -> Grow.

Topics Covered

  • ML Architecture
  • MLOps Foundations
  • Data Pipeline Architecture
  • Feature Store Design
  • Model Serving Infrastructure
  • vLLM
  • Kubeflow
  • Ray Serve
  • RAG Architecture
  • Fine-Tuning Strategy
  • Model Selection Methodology
  • ML Platform Engineering
  • Build vs Buy ML
  • AI Stack Evaluation

Profiles & Links

Build ML that scales.

Book a free 30-minute ML architecture scope call with our experts. We review your stack and tell you exactly what to fix before it breaks at scale.

Talk to an Expert