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AI Platform Specialist (Python, LLMs/SLMs, Cloud)

Reposted 8 Days Ago
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In-Office
Hyderabad, Telangana, IND
Mid level
In-Office
Hyderabad, Telangana, IND
Mid level
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.
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Job Title

AI Platform Specialist (Python, LLMs/SLMs, Cloud)

Job Summary

We 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

Required SkillsMust-Have
  • 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
     
Good to Have
  • 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

What We Care Most About
  • 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 Level
  • Experience in Python / AI deployment / MLOps / DevOps
  • Prior experience with production AI systems preferred

Top Skills

AWS
Azure
Ci/Cd
Docker
GCP
Google Gemini
Hugging Face
Linux
Llms
Openai
Python
Rest Apis
Slms

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