AI Engineer

3 нед. назад

Малайзия

machine learningdeep learningcloudllmprompt engineeringragai agents

Hands-on AI Engineer building, designing, and deploying AI and Generative AI solutions for clients in Southeast Asia.

As an AI Engineer, you will be a hands-on builder, working on the design, development, and deployment of AI and Generative AI solutions for our clients.
You will work within multidisciplinary teams and collaborate directly with client stakeholders to transform business challenges and ideas into practical, scalable AI solutions.
Build & Deploy AI Solutions: Design, prototype, test, and deploy AI/ML and Generative AI solutions, from PoCs through to production.
Generative AI & LLMs: Develop solutions leveraging LLMs, RAG, embeddings, prompt engineering, AI agents, and other emerging GenAI capabilities.
Machine Learning: Develop and integrate machine learning and deep learning models using relevant frameworks and libraries.
Cloud & AI Engineering: Build and deploy solutions using GCP, Azure, or AWS , including cloud-native AI services and data pipelines.
Solution Development: Contribute to the architecture and development of scalable, secure, and maintainable AI solutions.
Productionisation: Support deployment, monitoring, optimisation, and integration of AI solutions into client environments.
Client Collaboration: Work with business and technology stakeholders to understand requirements and translate them into technical solutions.
Continuous Innovation: Keep up with developments across AI/ML, Generative AI, LLMs, MLOps/LLMOps, and cloud technologies and apply them to real business use cases.

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, AI/Machine Learning , or another relevant technical field.
Professional experience in AI Engineering, Machine Learning, Data Science, Software Engineering , or a related technical role.
Strong programming skills in Python and familiarity with SQL.
Hands-on experience developing Machine Learning and/or Generative AI solutions .
Experience with LLM-related technologies such as RAG, embeddings, prompt engineering, vector databases, or AI agents .
Familiarity with ML/AI frameworks and libraries such as PyTorch, TensorFlow, Hugging Face , or equivalent.
Experience with at least one major cloud platform: GCP, Azure, or AWS .
Good understanding of APIs, Git, software engineering practices, and the AI development lifecycle.
Strong analytical and problem-solving skills.
Good communication skills and the ability to collaborate with both technical and business stakeholders.

Work at the forefront of AI. Build real-world solutions using Machine Learning, Generative AI, LLMs, and emerging technologies.
Build, not just advise. Take ideas from experimentation and PoCs through to solutions that can be deployed and used by clients.
Work with multidisciplinary teams. Collaborate with Data Scientists, Data Engineers, Consultants, and AI specialists across Southeast Asia and 's global network.
Develop your skills. Gain exposure to different industries, technologies, and business challenges while continuously developing your technical and consulting capabilities.
Make an impact. Help leading organisations turn AI opportunities into practical solutions and measurable business outcomes.

is a global consulting firm specialising in Data & AI , dedicated to transforming data into measurable business impact. We combine business consulting with deep expertise in data, AI, analytics, and technology to help organisations accelerate their transformation.
Our multidisciplinary teams bring together consultants, data scientists, data engineers, AI engineers, and technology experts to deliver impactful solutions for leading organisations around the world.
As we continue to grow our Data & AI capabilities in Southeast Asia, we are looking for an AI Engineer to join our team in Kuala Lumpur, Malaysia .
Experience taking AI/GenAI solutions from PoC into production .
Experience with MLOps/LLMOps , model deployment, monitoring, and lifecycle management.
Experience with Docker, Kubernetes , CI/CD, or other DevOps technologies.
Experience with frameworks and platforms for developing LLM or agentic AI applications .
Experience with modern data platforms such as Databricks, Snowflake, or BigQuery .
Previous experience working in a consulting or client-facing environment .
Experience working on enterprise-scale Data & AI projects.