Website:
Job details:
We are looking for an AI Systems Builder — someone who can design, deploy, and scale production-grade AI systems.
Role Overview
This role focuses on:
AI Infrastructure
System Design
Scalable Architecture
Production Deployment
MLOps & Lifecycle Management
If you enjoy building real-world AI systems that handle live traffic and scale, this role is for you.
What You’ll Do
Build and deploy end-to-end AI systems (LLMs / GenAI applications)
Design scalable APIs, pipelines, and microservices
Work on model serving, latency optimization, and scaling
Implement RAG pipelines, embeddings, and vector search systems
Architect systems that handle production-level traffic and load
Optimize performance, cost, and reliability
Set up MLOps pipelines for model lifecycle (training → deployment → monitoring)
Implement model versioning, monitoring, and automated retraining workflows
MUST-HAVE REQUIREMENTS (Strict Filter)
1. AI / ML Experience
Built AI/ ML models OR used APIs like OpenAI
Experience in NLP / LLM / RAG / embeddings
2. Production Deployment Experience (MOST IMPORTANT)
Deployed AI/ML models in real production environments
Built REST APIs using FastAPI
Experience with Docker + Kubernetes
Worked on live systems (not just notebooks)
If your experience is limited to Kaggle or academic projects, do NOT apply
3. AI Infrastructure, Scaling & MLOps
Experience with distributed systems and scalability
Hands-on with AWS / GCP / Azure
Strong understanding of MLOps practices and model lifecycle management
Experience with:CI/CD for ML pipelines
Model versioning & experiment tracking (MLflow, etc.)
Monitoring model performance & drift
Automated deployment pipelines
Tools:
Kubernetes, Docker
AWS EC2 / SageMaker / Lambda
Redis, Kafka
CI/CD tools
4. System Design & Architecture
Designed scalable systems (not just coding tasks)
Experience making architecture decisions
Built systems that:Handle high traffic
Reduce latency
Improve performance
Bonus (Nice to Have)
Built LLM applications (ChatGPT, LangChain, RAG)
Experience in startups or production environments
Open-source contributions
Click on Apply to know more.