Build, deploy, and operate production AI platforms: productionize LLM/SLM APIs, fine-tune and serve Hugging Face models, containerize services, manage cloud deployments, CI/CD, monitoring, scaling, and cost optimization.
Job Title
AI Platform Specialist (Python, LLMs/SLMs, Cloud)
Job SummaryWe are looking for an AI Platform Specialist to build, deploy, and operate AI models in production. This role is deployment-focused, with emphasis on scalability, reliability, and cost efficiency.
You will work hands-on with Python, LLM/SLM APIs (OpenAI, Gemini), and open-source models (Hugging Face) to turn AI models into production-ready platforms and services.
Key Responsibilities- Deploy AI/ML models built in Python into production environments
- Productionize OpenAI, Gemini, and other LLM APIs
- Build, fine-tune, and deploy Small Language Models (SLMs)
- Work with Hugging Face models (loading, fine-tuning, inference, optimization)
- Build and maintain REST APIs for AI services
- Containerize and deploy applications using Docker
- Deploy and manage services on cloud platforms (AWS / GCP / Azure)
- Set up and maintain CI/CD pipelines
- Monitor latency, failures, and inference cost
- Manage model versioning, scaling, and rollbacks
- Strong Python (production experience)
- Experience deploying AI/ML systems into production
- Hands-on experience with OpenAI / Gemini / LLM APIs
- Experience with the Hugging Face ecosystem
- Understanding of SLMs and model optimization
- REST APIs and backend systems
- Docker and containerized deployments
- Cloud platforms (AWS / GCP / Azure)
- Linux and CI/CD workflows
- Kubernetes or serverless deployments
- MLOps tools (MLflow, DVC, Kubeflow)
- Monitoring and logging tools
- Experience optimizing LLM/SLM cost, latency, and memory
- Basic training or fine-tuning workflows
- Ability to deploy and operate AI platforms reliably
- Strong focus on simplicity, performance, and cost
- Hands-on, ownership-driven mindset
- Comfort working in a lean startup environment
- Experience in Python / AI deployment / MLOps / DevOps
- Prior experience with production AI systems preferred
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