AI Infrastructure Specialist

4 days ago

Vijayawada, Andhra Pradesh, India beBeeAI Full time ₹ 1,80,00,000 - ₹ 2,50,00,000
Senior AI Systems Architect

We're seeking an experienced AI systems architect to lead the development and deployment of large-scale AI solutions that meet business needs.

Key Responsibilities:

  • Design, develop, and deploy end-to-end AI systems using large language models and generative AI technologies.
  • Create scalable, production-ready AI applications that meet performance requirements.
  • Evaluate and integrate LLM APIs from leading providers.
  • Establish best practices for prompt engineering, model selection, and AI system optimization.
  • Fine-tune open-source models for specific business use cases.
  • Implement custom training pipelines and evaluation frameworks.
  • Optimize model performance, latency, and cost for production environments.
  • Stay current with the latest model architectures and fine-tuning techniques.
  • Deploy and manage AI models at enterprise scale using containerization and orchestration.
  • Build robust, scalable APIs using FastAPI and similar frameworks.
  • Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment.

Besides these responsibilities, the ideal candidate should possess a strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques.

Required Qualifications:

  • 7+ years of experience in machine learning engineering or data science.
  • Proven track record of delivering large-scale ML solutions.
  • Expert-level proficiency with LLM APIs.
  • Hands-on experience fine-tuning transformer models.
  • Strong proficiency in FastAPI, Docker, and Kubernetes.
  • Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers).
  • Proficiency in Python and modern software development practices.
  • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services.

Core Competencies:

  • Ability to translate complex business requirements into technical solutions.
  • Strong problem-solving skills and architectural thinking.

Preferred Qualifications:

  • Experience with vector databases and retrieval-augmented generation systems.
  • Knowledge of distributed training and model parallelization techniques.
  • Experience with model quantization and optimization for edge deployment.
  • Familiarity with AI safety, alignment, and responsible AI practices.

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