AI Associate/Engineer (On‑Site)

About the role

iLabs is seeking an AI Associate/Engineer to design, develop, train, and deploy machine‑learning models on‑site in Battaramulla. You will work with cutting‑edge technologies such as large language models, retrieval‑augmented generation, and generative AI to create intelligent solutions for a variety of industries.

Key responsibilities

• Design, develop, train, and deploy AI/ML models using Python or Scala.
• Build AI solutions leveraging deep learning, LLMs, RAG, and generative AI.
• Create Agentic AI applications that automate workflows in DevOps, customer support, and enterprise operations.
• Collaborate with engineering and product teams to embed AI capabilities into software products and enterprise systems.
• Prepare, preprocess, and analyze large datasets for feature engineering, model training, validation, and evaluation.
• Develop APIs and backend services to support AI models and intelligent agents.
• Implement MLOps practices, including model deployment, monitoring, versioning, and continuous improvement.
• Optimize AI solutions for scalability, accuracy, performance, and production readiness.
• Translate business requirements into practical AI solutions that deliver measurable value.
• Stay current with emerging AI/ML technologies, Agentic AI frameworks, LLMs, and industry best practices.

Required profile

• Bachelor’s degree in Computer Science, Software Engineering, AI, Machine Learning or a related field.
• 1‑3 years of hands‑on experience developing, training, and deploying AI/ML models.
• Proficiency in Python; Scala is a plus.
• Experience with AI/ML frameworks and model lifecycle management.
• Understanding of LLMs, Retrieval‑Augmented Generation, Generative AI, or NLP technologies.
• Familiarity with Agentic AI concepts, AI workflow orchestration, REST APIs, microservices, and data pipelines.

Required skills

• Python
• Scala (advantage)
• AI/ML frameworks (e.g., TensorFlow, PyTorch)
• Large Language Models (LLMs)
• Retrieval‑Augmented Generation (RAG)
• Generative AI
• Natural Language Processing (NLP)
• Agentic AI
• REST API development
• Microservices architecture
• Data pipelines
• MLOps practices