AI/ML Engineer (Generative AI & LLMs)

Job Summary

We are seeking a talented AI/ML Engineer to design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and modern machine learning techniques. The ideal candidate will have strong experience in transformer-based models, LLM engineering, scalable backend systems, and cloud-based AI infrastructure.

You will play a key role in building intelligent platforms that leverage Generative AI, retrieval-augmented systems, and scalable microservices architectures to deliver impactful AI-driven solutions.

Responsibilities

AI / ML Development

• Design and build AI-powered applications using transformer-based Large Language Models (LLMs).
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for context-aware AI systems.
• Implement prompt engineering techniques to improve LLM accuracy and performance.
• Apply techniques to reduce hallucinations and improve model reliability.

LLM Engineering

• Build end-to-end LLM pipelines using LangChain or LlamaIndex.
• Integrate vector databases for semantic search and contextual retrieval.
• Develop AI workflows involving multiple model interactions and tool integrations.
• Contribute to improving LLM evaluation and monitoring frameworks.

Backend Platform Development

• Develop scalable Python-based backend services for AI applications.
• Design and implement REST APIs for AI-driven systems.
• Build systems using microservices architecture and distributed systems principles.

Data Infrastructure Scalability

• Implement scalable pipelines using Redis, message queues (Pub/Sub or Kafka), and caching mechanisms.
• Architect backend systems capable of handling large-scale user traffic and AI workloads.
• Ensure system performance, reliability, and efficient resource utilization.

Cloud Deployment

• Deploy and manage AI systems on Google Cloud Platform (preferred) or AWS/Azure.
• Work with cloud-native infrastructure for model deployment, scaling, and monitoring.

Collaboration

• Collaborate with product managers, data scientists, and engineering teams to translate business requirements into AI solutions.
• Participate in architecture discussions and technical decision-making.
• Continuously explore and adopt latest advancements in AI and Generative AI technologies.

Requirements

Education

Bachelor s or Master s degree in:

• Computer Science
• Artificial Intelligence.
• Machine Learning.
• Data Science.

or equivalent practical experience in AI/ML engineering.

Experience

• 2+ years of experience working with AI/ML or LLM-based systems

AI / Machine Learning

• Strong understanding of Transformer architecture.
• Experience working with Large Language Models (LLMs).
• Knowledge of RNNs, LSTMs, and the evolution toward transformer-based architectures.
• Understanding of Reinforcement Learning from Human Feedback (RLHF).

LLM Engineering

• Prompt engineering.
• Retrieval-Augmented Generation (RAG) pipelines.
• Experience with LangChain or LlamaIndex.
• Experience working with vector databases.

Backend Systems

• Python programming.
• Building REST APIs.
• Microservices architecture.
• Distributed systems design.

Data Infrastructure

• Redis.
• Message queues such as Google Pub/Sub or Kafka.
• Designing scalable backend systems.

Cloud Platforms

• Google Cloud Platform (preferred).
• Experience with AWS or Azure also acceptable.

Good to Have

• Experience building AI developer tools or AI platforms.
• Knowledge of test automation frameworks.
• Experience with LLM evaluation frameworks.
• Familiarity with MLOps pipelines and model lifecycle management.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.