Top Machine Learning Jobs in Malaysia

The Director of Credit Risk Business Development will partner with clients to drive analytics and credit risk strategies, lead sales initiatives, and ensure successful analytics project implementations while achieving sales targets.

Participate in a 12-month new-grad development program to improve test equipment efficiency, introduce predictive maintenance, sunset legacy tools, reduce costs through lean methods, and develop automation/AI solutions to enhance tool performance and reliability.

The Analyst, Cloud Application Transformation will gather user requirements, analyze data, support documentation, and facilitate communication between business and development teams.

The role leads data and AI strategy for BSC APAC, overseeing data governance and AI solutions to drive business value and digital transformation.

The Senior Gen AI Engineer leads the design and strategy for Generative AI use cases, focusing on user research, product management, and collaboration with cross-functional teams to drive AI innovations and solutions.

This role involves leading AI use case discovery and strategy, user research, product concepting, and prioritization of AI initiatives, ensuring alignment with customer needs and business value.

Perform remote part-time data tasks to improve Malay AI content, including data collection, evaluation, annotation, pairwise comparisons, counting, and object tagging across audio, video, images, and collected data.

Develop, implement and maintain credit risk models (scorecards, IRM, IFRS9 ECL, stress testing, economic capital, ML). Monitor model performance, manage governance and validation, engage auditors/regulators, and deliver model outputs for credit decisioning, allowance and capital assessment.

The AI/ML Engineer develops and integrates AI models into production systems, optimizing performance and supporting project teams with leadership and mentorship.

Drive net-new enterprise sales of digital transformation solutions for logistics and supply chain customers. Prospect and close high-value deals, co-sell with hyperscalers, lead complex negotiations, coordinate cross-functional teams, and position AI/IDP/automation solutions to modernize logistics workflows.

Designs and executes cybersecurity system integration tests for software and hardware, develops automation scripts and maintains test infrastructure, troubleshoots failures, manages defects, and integrates AI/ML to improve automation solutions while documenting processes and collaborating across engineering teams.

Work with Product, Business, and Engineering to collect, clean, analyze data, build Python and SQL automation, contribute to internal analytics platforms, assist cloud deployments, and document technical solutions to support decision-making.

As an AI Data Specialist, you will support AI-generated content improvement in Chinese Simplified through tasks like data collection, evaluation, and annotation.

The Fraud Ops Sr Analyst manages fraud losses, develops policies, and analyzes risks associated with digital banking. Responsibilities include fraud detection, data analysis, collaboration with tech teams, and leadership development.

Own and scale APAC programmatic advertising strategy to drive user acquisition, retention, and ROAS. Lead media buying across auctions, PMPs, preferred deals and PG; leverage AI/ML and automation; set best practices for targeting, frequency, remarketing, brand safety and DCO; research and scale emerging channels like CTV, audio, contextual and DOOH.

Build and maintain user tagging and profiling systems, analyze large-scale behavior data, perform feature engineering and exploratory analysis, support cross-functional teams for segmentation, monitor tag effectiveness, detect anomalies and fraud patterns, and improve data methodologies to enable risk control and personalized services.

Lead a Data Analyst team to analyze PB-scale transactional and customer data, build algorithmic systems and visualizations, implement ML/LLM solutions for compliance use cases, support business stakeholders with data requests, and translate findings into actionable recommendations.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Lead AI and analytics initiatives for substrate plating, washing, and polishing manufacturing. Monitor and optimize plating processes, control contamination, manage chemicals and inventory, improve OEE, define KPIVs/KPOVs, build dashboards, apply SPC and machine learning models for prediction and anomaly detection, and collaborate with data engineers to integrate sensor and equipment data.