101 Generative AI jobs in Malaysia

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DRAIVER is an industry disruptor pioneering a best-in-class AI logistics platform that enables vehicle movement planning, coordination, and execution. We streamline management by connecting businesses to transport services and independent contract drivers, simplifying employment with quick and direct access to jobs and drivers. Our contract driver network comprises thousands of associates servicing clients ranging from large Multi-National Fleet and Rental Companies, OEMs, and Large Automotive Groups to small businesses with a single location.

We are currently hiring a highly skilled and motivated Generative AI Engineer to join our talented engineering team. As a Generative AI Engineer, you will develop and implement generative AI solutions to solve complex problems and drive innovation across our organization.

• Develop AI/ML solutions from inception to deployment using Python and state-of-the-art LLM/GenAI frameworks.
• Prototype and build proof of concepts (POCs) to demonstrate feasibility and value.
• Research and develop innovative applications of LLMs to address real-world challenges.
• Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with business goals.
• Create clear documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.

• Bachelor’s Degree or current enrollment in a final course, majoring in Statistics, Applied Mathematics, Computer Science, or a related field.
• At least 1 year of hands-on experience with Python.
• Strong background in NLP and experience working with Large Language Models (LLMs) such as GPT-4, Claude, or Gemini, with familiarity with platforms like OpenAI API, Hugging Face Transformers, LangChain, and PyTorch.
• Proven ability to develop scalable API solutions and perform prompt engineering.
• Excellent communication skills in English, capable of explaining complex LLM capabilities and limitations to non-technical stakeholders.

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• Entry level

• Full-time

• Engineering and Information Technology

• Internet Publishing

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We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit , and read about the latest news via our StoryHub .

We are seeking an experienced and innovative AI Development Architect to lead the development of Lenovo’s AI technology platform. This role is responsible for designing and delivering core AI infrastructure components, including GenAI-based model development platforms, enterprise knowledge & data platform, and intelligent agents. The ideal candidate will combine strong software engineering skills with deep expertise in GenAI technologies to drive scalable, intelligent solutions across Lenovo’s product ecosystem.

Key Responsibilities:
1. Product Development & Technical Leadership:
Lead the design and development of Lenovo’s AI technology platform, including GenAI-powered model training and inference pipelines, RAG-based knowledge systems, and intelligent agents.
Collaborate with product and other teams to integrate AI capabilities into enterprise products and services.
Evaluate and adopt leading GenAI frameworks, tools, and best practices to accelerate innovation.

2. Global Team Collaboration:
Partner with global engineering teams in Malaysia, Singapore, and other locations to drive AI infrastructure development.
Establish standards and reusable components to ensure consistency and reusability across projects.
Mentor engineers and promote cross-functional collaboration in AI solution design.

3. Customer & Business Support:
Work with solution and product teams to define and deliver customer-specific AI solutions.
Participate in technical consulting, POCs, and real-world deployment of AI applications.

Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 8+ years of experience in enterprise software development, with at least 3 years of hands-on experience in AI/ML or GenAI platform architecture.
- Strong programming proficiency in Java and Python, with solid experience in Spring and Spring Cloud frameworks.
- Familiarity with relational databases such as PostgreSQL and MySQL.
- Hands-on experience with Docker, Kubernetes, Git, and modern CI/CD pipelines.
- Solid understanding of DevOps practices and Scrum-based agile development.
- In-depth knowledge of GenAI technologies including transformers, fine-tuning, inference, RAG (Retrieval-Augmented Generation), and agent frameworks.
- Experience with GenAI tools such as LangChain, LangGraph, or similar open-source frameworks.
- Demonstrated success in delivering real-world GenAI applications such as AI assistants, copilots, content generation tools, or knowledge bots.
- Familiarity with LLM serving, vector databases, and open-source model integration is a strong plus.
- Excellent communication and collaboration skills; fluent in English and experienced working in global, cross-functional teams.

If you require an accommodation to complete this application, please

Job Summary:
The AI Development Team Lead is responsible for managing and mentoring a team of AI engineers, ML developers, and data scientists. This role bridges strategic objectives from the Head of Department (HOD) with execution by the technical team. The ideal candidate combines technical AI/ML expertise with project management and people leadership to ensure the successful delivery of AI initiatives that align with business goals.

Key Responsibilities:
Strategic Planning & Execution
• Collaborate with HOD to define AI vision, goals, and KPIs aligned with business needs.
• Translate high-level strategy into actionable technical tasks and sprint plans.
• Evaluate and recommend AI technologies, platforms, tools, and best practices.
Team Leadership & Management
• Lead, mentor, and manage a multidisciplinary team (AI engineers, ML specialists, data scientists).
• Conduct regular one-on-ones, performance reviews, and skill gap assessments.
• Promote a collaborative, transparent, and accountable team environment.
Technical Oversight
• Oversee design, development, testing, deployment, and maintenance of AI/ML models.
• Perform code reviews, model validation, and ensure adherence to engineering standards.
• Identify and resolve technical bottlenecks, support experimentation and innovation.
Project Management
• Manage project timelines, resource allocation, risk assessments, and reporting.
• Facilitate Agile ceremonies (sprint planning, stand-ups, retrospectives).
• Monitor and report on progress, blockers, and deliverables to HOD and stakeholders.
Cross-Functional Collaboration
• Work closely with product managers, data engineers, software teams, and business stakeholders.
• Ensure AI models and systems integrate well with broader platforms or customer touchpoints.
• Translate business questions into data science problems and actionable models.
Governance, Ethics & Compliance
• Ensure all AI/ML developments comply with data privacy laws and AI ethics standards.
• Define policies for model retraining, versioning, and explainability.

Qualifications & Skills:
Education:
• Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Certifications in AI/ML (e.g., Google AI, AWS ML, Microsoft AI Engineer) are a plus.
Experience:
• 5–8 years total in AI/ML, with 2–3 years in a leadership or technical management role.
• Proven experience in deploying ML models into production (real-time or batch).
• Familiarity with Agile/Scrum practices and tools like Jira, Confluence, Git, etc.
Technical Proficiency:
• Proficient in Python and ML libraries: TensorFlow, PyTorch, scikit-learn, etc.
• Experience with model lifecycle: training, tuning, deployment, and monitoring.
• Strong understanding of supervised/unsupervised learning, NLP, computer vision, or generative AI.
• Familiarity with MLOps: Docker, Kubernetes, MLFlow, CI/CD for AI pipelines.
• Experience working with cloud platforms: AWS, GCP, Azure.
Soft Skills:
• Excellent communication and stakeholder management skills.
• Strong leadership, team-building, and conflict resolution skills.
• Analytical mindset with attention to both big-picture strategy and technicaldetail.

Job Summary:
The AI Development Team Lead is responsible for managing and mentoring a team of AI engineers, ML developers, and data scientists. This role bridges strategic objectives from the Head of Department (HOD) with execution by the technical team. The ideal candidate combines technical AI/ML expertise with project management and people leadership to ensure the successful delivery of AI initiatives that align with business goals.

Key Responsibilities:
Strategic Planning & Execution
• Collaborate with HOD to define AI vision, goals, and KPIs aligned with business needs.
• Translate high-level strategy into actionable technical tasks and sprint plans.
• Evaluate and recommend AI technologies, platforms, tools, and best practices.
Team Leadership & Management
• Lead, mentor, and manage a multidisciplinary team (AI engineers, ML specialists, data scientists).
• Conduct regular one-on-ones, performance reviews, and skill gap assessments.
• Promote a collaborative, transparent, and accountable team environment.
Technical Oversight
• Oversee design, development, testing, deployment, and maintenance of AI/ML models.
• Perform code reviews, model validation, and ensure adherence to engineering standards.
• Identify and resolve technical bottlenecks, support experimentation and innovation.
Project Management
• Manage project timelines, resource allocation, risk assessments, and reporting.
• Facilitate Agile ceremonies (sprint planning, stand-ups, retrospectives).
• Monitor and report on progress, blockers, and deliverables to HOD and stakeholders.
Cross-Functional Collaboration
• Work closely with product managers, data engineers, software teams, and business stakeholders.
• Ensure AI models and systems integrate well with broader platforms or customer touchpoints.
• Translate business questions into data science problems and actionable models.
Governance, Ethics & Compliance
• Ensure all AI/ML developments comply with data privacy laws and AI ethics standards.
• Define policies for model retraining, versioning, and explainability.

Qualifications & Skills:
Education:
• Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Certifications in AI/ML (e.g., Google AI, AWS ML, Microsoft AI Engineer) are a plus.
Experience:
• 5–8 years total in AI/ML, with 2–3 years in a leadership or technical management role.
• Proven experience in deploying ML models into production (real-time or batch).
• Familiarity with Agile/Scrum practices and tools like Jira, Confluence, Git, etc.
Technical Proficiency:
• Proficient in Python and ML libraries: TensorFlow, PyTorch, scikit-learn, etc.
• Experience with model lifecycle: training, tuning, deployment, and monitoring.
• Strong understanding of supervised/unsupervised learning, NLP, computer vision, or generative AI.
• Familiarity with MLOps: Docker, Kubernetes, MLFlow, CI/CD for AI pipelines.
• Experience working with cloud platforms: AWS, GCP, Azure.
Soft Skills:
• Excellent communication and stakeholder management skills.
• Strong leadership, team-building, and conflict resolution skills.
• Analytical mindset with attention to both big-picture strategy and technicaldetail.