About This Role

<h3>Job Title</h3><p style="line-height:1.38;margin-top:16px;margin-bottom:16px;">AI Platform Specialist (Python, LLMs/SLMs, Cloud)</p><hr><h3>Job Summary</h3><p style="line-height:1.38;margin-top:16px;margin-bottom:16px;">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.</p><p style="line-height:1.38;margin-top:16px;margin-bottom:16px;">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.</p><hr><h3>Key Responsibilities</h3><ul><li style="list-style-type:disc;">Deploy AI/ML models built in Python into production environments</li><li style="list-style-type:disc;">Productionize OpenAI, Gemini, and other LLM APIs</li><li style="list-style-type:disc;">Build, fine-tune, and deploy Small Language Models (SLMs)</li><li style="list-style-type:disc;">Work with Hugging Face models (loading, fine-tuning, inference, optimization)</li><li style="list-style-type:disc;">Build and maintain REST APIs for AI services</li><li style="list-style-type:disc;">Containerize and deploy applications using Docker</li><li style="list-style-type:disc;">Deploy and manage services on cloud platforms (AWS / GCP / Azure)</li><li style="list-style-type:disc;">Set up and maintain CI/CD pipelines</li><li style="list-style-type:disc;">Monitor latency, failures, and inference cost</li><li style="list-style-type:disc;">Manage model versioning, scaling, and rollbacks</li></ul><hr><h3>Required Skills</h3><h3 style="line-height:1.38;margin-top:19px;margin-bottom:5px;">Must-Have</h3><ul><li style="list-style-type:disc;">Strong Python (production experience)</li><li style="list-style-type:disc;">Experience deploying AI/ML systems into production</li><li style="list-style-type:disc;">Hands-on experience with OpenAI / Gemini / LLM APIs</li><li style="list-style-type:disc;">Experience with the Hugging Face ecosystem</li><li style="list-style-type:disc;">Understanding of SLMs and model optimization</li><li style="list-style-type:disc;">REST APIs and backend systems</li><li style="list-style-type:disc;">Docker and containerized deployments</li><li style="list-style-type:disc;">Cloud platforms (AWS / GCP / Azure)</li><li style="list-style-type:disc;">Linux and CI/CD workflows</li></ul><h3 style="line-height:1.38;margin-top:19px;margin-bottom:5px;">Good to Have</h3><ul><li style="list-style-type:disc;">Kubernetes or serverless deployments</li><li style="list-style-type:disc;">MLOps tools (MLflow, DVC, Kubeflow)</li><li style="list-style-type:disc;">Monitoring and logging tools</li><li style="list-style-type:disc;">Experience optimizing LLM/SLM cost, latency, and memory</li><li style="list-style-type:disc;">Basic training or fine-tuning workflows</li></ul><hr><h3>What We Care Most About</h3><ul><li style="list-style-type:disc;">Ability to deploy and operate AI platforms reliably</li><li style="list-style-type:disc;">Strong focus on simplicity, performance, and cost</li><li style="list-style-type:disc;">Hands-on, ownership-driven mindset</li><li style="list-style-type:disc;">Comfort working in a lean startup environment</li></ul><hr><h3>Experience Level</h3><ul><li style="list-style-type:disc;">Experience in Python / AI deployment / MLOps / DevOps</li><li style="list-style-type:disc;">Prior experience with production AI systems preferred</li></ul><p>Originally posted on <a href="https://himalayas.app">Himalayas</a></p>

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 Skills

Must-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

Originally posted on Himalayas