Job Description

About Us:

POSable is a leading provider of innovative retail solutions, dedicated to helping our clients transform their data into actionable insights. With a strong focus on the retail sector, we pride ourselves on delivering top-notch business intelligence services that drive growth and operational efficiency.

With the integration of AI technology, we are pushing the boundaries of innovation to enhance our products' Unique Selling Proposition (USP). We are looking for a highly skilled, hands-on and passionate

Machine Learning Engineer / Developer

to join our dynamic team. This role is an exciting opportunity to build high-performing ML models and apply AI-driven analytics in the retail industry.

:

As a Machine Learning Engineer / Developer

, you will be responsible for designing, developing, and deploying AI/ML models that drive valuable insights for our retail and POS solutions. You will work closely with data engineers, BI specialists, and business teams to enhance our product offerings, leveraging AI to optimize decision-making for our customers.

Key Responsibilities:

Design, develop, and optimize machine learning models with a proven track accuracy rate of

95% or higher

. Work with

large datasets

to clean, preprocess, and structure data for AI/ML applications. Build and maintain scalable machine learning pipelines that can be deployed in a

cloud

environment. Optimize models for performance, efficiency, and scalability in production. Develop AI-driven insights and predictive analytics for the retail industry, aligning models with business needs. Implement machine learning algorithms for demand forecasting, customer segmentation, recommendation systems, fraud detection, and other AI applications. Collaborate with data engineers, software developers, and BI teams to integrate ML models into existing systems. Monitor and maintain model performance, retraining as necessary to ensure optimal accuracy. Stay up-to-date with the latest advancements in AI, ML, and data analytics to drive continuous innovation.

Skills & Qualifications:

2-3+ years

of hands-on experience in developing, training, and deploying high-performing machine learning models. Strong proficiency in

Python

and libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy. Experience working with

data frames, feature engineering,

and

data preprocessing

for ML models. Proven track record of optimizing ML models for performance, accuracy, and efficiency. Experience in deploying models on cloud platforms such as

Azure, Snowflake, AWS, or GCP

. Solid understanding of

business analytics

and

retail industry data

, with the ability to translate data insights into business value. Experience working with structured and unstructured data, handling real-time and batch processing. Knowledge of

MLOps

practices and

CI/CD

pipelines for machine learning. Strong problem-solving and analytical skills with the ability to work independently and in a team. Experience with any

Azure ML, AWS SageMaker, or GCP AI Platform

. Background in building recommender systems, classification, fraud detection models, or demand forecasting in the retail industry. Familiarity with BI tools like

Power BI

is a plus. Understanding of deep learning and NLP techniques.

Why Join Us:

Opportunity to be part of a forward-thinking team integrating

AI into POS and BI solutions

.

Innovative Environment:

Work with a team of passionate data professionals dedicated to innovation and excellence.

Professional Growth:

Opportunities for continuous learning, development, and career advancement.

Impactful Work:

Make a significant impact by helping retail clients harness the power of their data to drive business success.

Competitive Compensation:

Attractive salary package with benefits including health insurance, retirement plans, and more.
Job Type: Full-time

Pay: RM7,000.00 - RM11,000.00 per month

Benefits:

Free parking Health insurance Maternity leave Opportunities for promotion Parental leave Professional development Vision insurance
Schedule:

Day shift Monday to Friday
Work Location: On the road