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Applied AI Engineer - 2
LinkEyeTumkur, IN7 days ago
Job descriptionBachelor's or Master's degree in Computer Science, AI, or a related field. 3+ years of professional experience in a machine learning and / or applied AI developer Strong proficiency in Python and hands-on experience with ML / DL frameworks like PyTorch or TensorFlow Strong understanding of machine learning, artificial neural networks, and deep learning. Proven experience building applications using LLMs and a deep understanding of concepts like prompt engineering, fine-tuning, and RAG. Practical experience with agentic or application frameworks like LangGraph, LangChain, or similar Experience deploying and maintaining ML models in a production environment using MLOps principles Excellent problem-solving skills and an ability to translate complex requirements into working software. Good understanding of networking fundamentals like TCP / IP, DNS, and networking devices such as router, firewall etc. Familiarity with tech stack that is used for building observability platform such as kafka, clickhouse, ETL pipelines etc
About Us
We are a Bangalore based networking startup building network observability and co-pilot system to improve the network reliability and reduce the time to action for our customers. The founding team has a cumulative 45 years of experience in networking industry.
Role Overview
As an Applied AI Engineer-II, you will be joining the founding member of AI team, responsible for building the intelligence part of our platform. You will not only be experimenting with building models but also shipping the production grade AI agents that solves the real-world use cases in network assurance.
Responsibility
- Design, develop, and ship robust AI agents using Large Language Models (LLMs) and agentic frameworks
- Collaborate closely with our founding team and networking experts to encode network L1 and L2 engineering expertise into effective, multi-step AI agent workflows.
- Establish baseline and scientific evaluation frameworks to measure and enhance performance.
- Design and implement strategies for continuous model improvement, feedback collection and data collection strategies.
- Build an automated system to detect model drift and continuously retrain models
- Fine-tune models on domain-specific data, building sophisticated RAG (Retrieval-Augmented Generation), and develop LinkEye as an MCP server
- Partner with DevOps and Platform engineers to ensure your AI services are scalable, reliable, and seamlessly integrated into our product
Requirements
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Applied Ai Engineer • Tumkur, IN