Gabeo.ai
India
Entry-Level Machine Learning Engineer (LLM & AI Agent Specialization) - Healthcare Revenue Cycle AI
Machine Learning Full-time Associate 1w ago
- AI
- Machine Learning
- Python
- Pytorch
AI Summary
Build and optimize generative AI agents and LLM-powered systems at Refold AI. Implement memory, RAG pipelines, prompt engineering, model training, and scalable cloud deployments. Requires 5+ years in AI/ML with deep LLM experience and 1-2 years backend SDE experience.
Key Highlights
Implement memory and context management for AI agents
Build RAG pipelines integrating LLMs with real-time data
Apply prompt engineering, transfer learning, and custom model training
Optimize model performance and cost in production
Deploy scalable models on cloud platforms with Docker and Kubernetes
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Key Responsibilities
Implement memory for AI Agents, ensuring proper context management
Apply retrieval-augmented generation (RAG) pipelines to integrate LLMs with real-time data and context
Apply advanced techniques in prompt engineering, transfer learning, and custom model training
Optimise model performance and cost across production environments
Work with tools like Hugging Face, LangChain, OpenAI APIs, and vector databases (FAISS, Pinecone, Weaviate)
Deploy scalable models using cloud platforms like AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes
Collaborate with global teams and researchers in a fast-paced, remote-first setup
Technical Skills Required
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Nice to Have
Preferably from Tier 1 colleges with a background in CSE preferred
Job Description
About Refold AI
Refold AI is the AI integration platform built for agents, made for modern SaaS companies that need to ship enterprise integrations at scale. We're reimagining integrations with AI agents that work like business consultants and integration engineers, building them 10x faster, in hours instead of days. The payoff: integrations stop being a bottleneck that costs you deals and burns margin, and become a growth engine. You win the enterprise deals that hinge on them, onboard faster, and scale without an army of consultants.
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