Specialist, Gen AI Engineer

U MobileKuala Lumpur, Kuala Lumpur, Malaysia

30+ hari lalu

Penerangan pekerjaan

U Mobile, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Life at U Mobile

We are Passionate, Innovative, Trustworthy, Team-Oriented & Fun-Loving. Let’s start your journey with an award-winning organization!

Top Reasons to Join Us

Awarded For Most Preferred Employers in Telecommunication Industry (2022, 2023 & 2024)
Bronze Winner in Cross-Generational Workforce Engagement (2024)
Gold Winner for Excellence in Workplace Culture (2021)
Comprehensive medical, dental, optical and insurance benefits
Flexi working hours arrangements
Staff Line & Device Subsidy
Smart Casual Attire
Child Parental Care Leave
Convenient location with access to public transport (Imbi Monorail / Bukit Bintang MRT)
Special employee discounts for selected F&B Brands

Role

Job Summary

The Gen AI Engineer will be supporting the development and implementation of generative AI solutions across the business. The role involves identifying suitable use cases, integrating large language models (LLMs), prompt pipelines, and retrieval-augmented generation (RAG) systems, and working with structured and unstructured data to enhance model performance. This role will also assist in embedding AI-generated insights into internal operations and customer-facing applications, contributing to improved efficiency and innovation.

Job Responsibilities

AI Solution Adoption and Integration : Assist in the implementation and integration of generative AI solutions, including large language models (LLMs), RAG systems, and prompt engineering tools. Contribute to testing and optimization efforts to ensure outputs are accurate and relevant to business needs.

Data Preparation for AI Models : Ingest, clean, and preprocess structured and unstructured data (e.g., text, documents, logs) for use in generative AI applications. Ensure data inputs are appropriately formatted and optimized for language model consumption.

Data Security and Governance : Comply with PDPA and internal data governance policies when handling sensitive or personal data. Ensure all AI-related processes adhere to the organization’s data protection and security standards.

Model Output Evaluation and Monitoring : Monitor the performance of generative AI outputs, flag issues such as hallucinations or inconsistencies, and support the evaluation of output quality. Provide feedback to support continuous improvement.

Collaboration with Cross-Functional Teams : Work closely with cross-functional teams—such as product, engineering, and analytics—to support the development of AI-driven use cases. Help translate user or business needs into actionable inputs for the AI team.

Continuous Learning and Development : Keep up to date with developments in generative AI technologies, tools, and techniques. Participate in knowledge-sharing sessions and contribute to the team's collective learning.

Other duties : Provide regular reporting on task and project status, including timely escalation of issues where necessary. Perform any other duties or responsibilities assigned by the Section Head or the Head of Department.

Qualifications

Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computational Linguistics, Mathematics, or a related technical field.

Fresh graduates or candidates with at least 1 year of experience in generative AI, machine learning, NLP, or software development, with exposure to real world AI applications. Experience in handling unstructured data or building AI-powered tools is a plus.

Familiarity with foundational models (e.g., GPT, LLaMA, Claude) and understanding how to apply them in real-world use cases.

Ability to design, test, and optimize prompts to guide language model outputs effectively, including few-shot and zero-shot techniques.

Strong proficiency in Python, with experience using GenAI-related libraries such as Hugging Face Transformers, LangChain, or LlamaIndex.

Experience deploying generative models via APIs or within applications, and integrating them with data sources and external tools.

Skills in preparing unstructured data (e.g., text, documents, chats) for use in generative AI pipelines.

Ability to test outputs for quality, factuality, and performance using human evaluation or automated metrics.

Familiarity with deploying AI models using tools such as Docker, FastAPI, and cloud platforms (AWS / GCP / Azure).

Interest in exploring the latest generative AI papers, tools, and techniques to drive practical innovation.

Strong ability to explain GenAI concepts and limitations clearly to both technical and non-technical stakeholders.

Analytical thinking with a focus on designing AI-driven solutions that are practical, scalable, and impactful.

Eagerness to stay updated with fast-evolving developments in generative AI and LLMs.

Comfortable working cross-functionally with engineers, analysts, product teams, and business stakeholders.

A strong drive to explore new GenAI techniques, tools, and applications in a rapidly evolving field.

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