AI Engineer

Hitachi eBworx; Selangor; On-site; MYR 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Bonuses

Training programs

Career growth

Job summary

Hitachi eBworx is seeking an experienced AI Engineer to design scalable AI/ML systems for financial and enterprise applications. You will work with LLMs, fine-tune models, and develop Agentic AI solutions in production environments.

In this role, you will collaborate with cross‑functional teams, optimize training pipelines, and leverage open‑source models and cloud infrastructure to deliver robust AI capabilities at scale.

Qualifications

• Experience with LLM fine-tuning and training (e.g., Hugging Face, Claude API).
• Strong understanding of Transformer models and NLP architectures.
• Expertise in reinforcement learning and self-supervised learning.
• Hands-on experience with RLHF (Reinforcement Learning from Human Feedback).

Responsibilities

• Design and develop scalable AI/ML models and pipelines for a variety of applications.
• Fine-tune large language models using supervised learning and alignment techniques such as DPO, ORPO and RLHF.
• Train and evaluate embedding models to improve downstream task performance.
• Integrate structured and unstructured data sources to enhance AI-driven decision-making.
• Improve model accuracy, contextual coherence, and response quality in generative AI outputs.
• Develop and optimize training, evaluation, and deployment pipelines for production environments.
• Leverage and fine-tune open-source AI models for specific use cases.
• Collaborate with cross-functional teams to deploy models at scale in real-world systems.

Skills

LLM fine-tuning

Transformer models

Reinforcement learning

Python

PyTorch or JAX

APIs for AI systems

Tools

Hugging Face

LangGraph

Docker

Kubernetes

OpenAI API

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

We are seeking an experienced AI Engineer to design and optimize AI/ML systems, leveraging cutting‑edge artificial intelligence and machine learning techniques. In this role, you will work with large language models (LLMs), fine‑tune AI systems, and develop scalable Agentic AI solutions for financial and enterprise applications.
This is an exciting opportunity to be at the forefront of AI innovation, working with the latest advancements in natural language processing, reinforcement learning, and scalable AI infrastructure.

What Awaits You:

Latest Tools & Tech – Work with cutting‑edge technologies to stay ahead.

Career Growth – Access training programs for upskilling or reskilling to build your portfolio.

Great Pay & Perks – Competitive salary and bonuses to reward your expertise and contributions.

What You'll Do:

Design and develop scalable AI/ML models and pipelines for a variety of applications.

Fine‑tune large language models using supervised learning and alignment techniques such as DPO (Direct Preference Optimization), ORPO (Odds Ratio Preference Optimization) and RLHF (Reinforcement Learning from Human Feedback).

Train and evaluate embedding models to improve downstream task performance.

Integrate structured and unstructured data sources to enhance AI‑driven decision‑making.

Improve model accuracy, contextual coherence, and response quality in generative AI outputs.

Develop and optimize training, evaluation, and deployment pipelines for production environments.

Leverage and fine‑tune open‑source AI models for specific use cases.

Collaborate with cross‑functional teams to deploy models at scale in real‑world systems.

What We Need From You:

Core AI & ML Skills

Experience with LLM fine‑tuning and training (e.g., Hugging Face, Claude API).

Strong understanding of Transformer models and NLP architectures.

Expertise in reinforcement learning and self‑supervised learning.

Hands‑on experience with RLHF (Reinforcement Learning from Human Feedback).

Programming & Frameworks

Proficiency in Python, and experience with PyTorch, or JAX.

Familiarity with LLM in stateful agentic workflows and multi‑agent orchestration.

Familiarity with Agent SDKs (LangGraph), MCP and A2A protocols.

Strong skills in working with APIs for AI system integration (e.g., OpenAI, Anthropic, Hugging Face).

Experience with SQL, NoSQL and Vector‑based databases for data handling.

Familiarity with distributed computing and scalable ML model training.

Solid understanding of ETL pipelines for processing large‑scale datasets.

Experience deploying AI models in cloud environments (AWS, Azure, GCP).

Knowledge of containerization (Docker, Kubernetes) and MLOps practices.