AI Engineer

BIG Pharmacy Healthcare Sdn Bhd; Klang City; On-site; MYR 90,000 - 120,000; Full time

Job summary

A leading healthcare company in Klang, Selangor is seeking an experienced professional to lead AI initiatives, manage data pipelines, and provide technical leadership in AI projects. The ideal candidate should possess a degree in a relevant field, have prior experience in deploying AI models, and demonstrate strong proficiency in programming languages like Python, R, or Java. Excellent analytical and communication skills are essential to effectively collaborate with stakeholders and foster innovation within the organization.

Qualifications

• Strong experience with deploying AI or ML models into production environments.
• Understanding of MLOps, DevOps, and CI/CD for machine learning pipelines.
• Knowledge of AI ethics and responsible AI frameworks.

Responsibilities

• Drive organization's AI initiatives through design and implementation of intelligent systems.
• Oversee data pipeline from collection to preprocessing and storage.
• Train, validate, and fine-tune machine learning models.

Skills

Proficiency in Python

Proficiency in R

Proficiency in Java

Analytical mindset

Excellent communication skills

Collaboration abilities

Problem-solving skills

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, or related field

Tools

TensorFlow

PyTorch

Scikit-learn

SQL

Spark

Hadoop

Airflow

AWS

Azure

Google Cloud

Job description

BIG Pharmacy Healthcare Sdn Bhd – Klang, Selangor

AI Solution Development and Automation

Drive the organization’s AI initiatives through the design and implementation of intelligent systems and automation solutions.

Identify opportunities where AI can add business value and optimize existing processes.

Data Management and Preparation

Oversee the entire data pipeline, from data collection and cleaning to preprocessing and storage.

Ensure data integrity, consistency, and accessibility for machine learning and AI applications.

Collaborate with data engineers and analysts to create scalable and efficient data architectures.

Model Training, Evaluation, and Deployment

Train, validate, and fine-tune machine learning models for optimal performance.

Evaluate models using appropriate metrics and perform error analysis to improve accuracy.

Deploy AI models into production environments and integrate them with existing applications or business systems.

Integration and Maintenance

Work with software development teams to integrate AI solutions into broader IT systems and enterprise platforms.

Continuously monitor AI systems in production, ensuring performance stability, fairness, and reliability.

Troubleshoot issues and retrain models as new data becomes available.

Cross-Functional Collaboration

Collaborate with business stakeholders, project managers, and engineers to define AI strategies that align with organizational objectives.

Translate business challenges into technical solutions and communicate results effectively to non-technical audiences.

Research, Innovation & Application in Digital Health Space

Stay current on the latest developments in AI, machine learning, and generative AI.

Explore and experiment with emerging technologies (e.g., LLMs, transformers, reinforcement learning).

Recommend new tools, techniques, and frameworks to enhance productivity and innovation in the digital health space.

AI Ethics and Governance

Implement ethical and governance frameworks for responsible AI use.

Ensure transparency, fairness, and explainability in AI systems.

Address data privacy, bias mitigation, and security issues in model development and deployment.

Technical Leadership and Mentorship

Provide technical guidance to team members in AI, data science, and automation projects.

Conduct knowledge-sharing sessions and code reviews to promote best practices.

Foster a culture of continuous learning within the MIS or data team.

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Prior experience deploying AI or ML models into production environments. Understanding of MLOps, DevOps, and CI/CD for machine learning pipelines. Knowledge of AI ethics, compliance, and responsible AI frameworks.
• Strong proficiency in Python, R, or Java. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of data management tools (SQL, Spark, Hadoop, Airflow). Familiarity with cloud platforms (AWS, Azure, Google Cloud) for AI/ML deployment.
• Analytical and problem-solving mindset. Excellent communication and collaboration abilities. Ability to manage multiple projects and meet deadlines. Passion for innovation and continuous learning.