Top Machine Learning Jobs in Malaysia

Design, develop, test, integrate and maintain embedded firmware for enterprise HDDs. Implement drivers, data structures, algorithms and data path code (C/C++/Python). Work with SAS/SATA/PCIe interfaces, collaborate across hardware and software platforms (Windows/Linux), produce design documents, run CI/unit tests, and lead technical investigations to resolution.

Design, develop, test, integrate, and maintain firmware for enterprise HDDs. Implement data structures, algorithms, drivers and data paths in C/C++ and Python. Work with SAS, SATA, PCIe interfaces, collaborate across hardware and OS platforms (Windows/Linux), create design documents, run technical investigations, and follow unit test/CI best practices.

Design, develop, test, integrate, and maintain firmware for enterprise HDDs. Implement data structures, algorithms, drivers, and data paths in C/C++ and Python. Work with SAS, SATA, PCIe interfaces, collaborate across hardware and software, create design documents, and participate in technical investigations and CI-driven testing.

Support day-to-day business activities by gathering user requirements, analyzing data, creating documentation, and assisting in AI-related projects for a smoother communication between business and development teams.

Develop, review and monitor credit rating models for the wholesale banking portfolio. Work with large datasets, perform model development, testing, documentation, UAT, and regulatory submissions. Produce performance monitoring reports, engage business experts for insights, and improve model monitoring and automation.

Support the Polish Engineering team by assisting with development and implementation of manufacturing automation, programming and testing automated systems, collecting and analyzing process data, troubleshooting issues, documenting procedures, and researching emerging automation and data science technologies.

The Data Analyst role involves annotating emails, identifying malicious URLs, labeling data for AI training, ensuring process adherence, and supporting project management KPIs.

This Data Analyst role involves annotating and examining emails, identifying malicious links, labeling data for AI, and ensuring compliance with processes. The candidate will also monitor KPIs and assist project management.

Lead and expand a major financial-institution account by building C-suite relationships, designing enterprise SaaS solutions, negotiating multi-million-dollar deals, driving account growth, and influencing product strategy. Travel up to 50% and collaborate across sales, product, delivery, and marketing.

Lead planning, coordination, and delivery of clinical document translations. Manage vendors, stakeholders, budgets, timelines, and quality controls. Implement and evaluate AI-enabled translation tools and oversee SME post-editing to ensure regulatory-compliant, high-quality translations for clinical documents.

Design, build, and productionize ML models for credit scoring, fraud detection, and segmentation. Maintain model governance and documentation, develop scalable MLOps pipelines and monitoring, generate analytical insights and dashboards, and mentor junior data scientists while leading end-to-end data science initiatives.

Manage relationships with high-value customers and partners in Malaysia to drive new logo, renewal, and cross-sell revenue for Sophos. Qualify opportunities, build C-level and channel relationships, collaborate with Sales Engineering/Marketing/Channel, maintain Salesforce CRM and forecasts, attend events, and coach teammates while ensuring customer satisfaction.

Lead and optimize manufacturing operations using digital technologies (automation, analytics, simulation, ML). Serve as technical specialist and project lead, drive continuous improvement, mentor teams, support customers, and implement digital solutions to improve production efficiency, quality, and cost.

Design, build, deploy, and maintain production-grade AI/ML models and services, including Generative and Agentic AI, RAG solutions, MLOps pipelines, data pipelines, observability, and compliance with security and responsible AI guidelines while collaborating with stakeholders and engineering teams.

Design, build, and deploy scalable ML models and pipelines from research to production. Own feature engineering, model tuning, real-time prediction, MLOps automation, monitoring, and lifecycle management to solve visibility, forecasting, and freight audit problems.

Maintain and monitor ML models in production, automate and scale data pipelines and model serving, troubleshoot issues, collaborate with cross-functional teams, and promote MLOps best practices and standards.

Design, build, deploy and operate end-to-end ML pipelines on Databricks. Develop production-grade Python and Spark code, implement MLOps practices (MLflow, CI/CD, versioning, monitoring), ensure reproducibility, security and governance, monitor model/data performance, and collaborate with data science, engineering and product teams to deliver scalable, compliant ML services.

As a Lead Data Scientist, you'll manage end-to-end projects, build and deploy AI models, analyze data, and collaborate with teams to enhance user experience.

Contribute to the design and rollout of ML & AI platforms. Write production code and develop scalable ML pipelines and automation.

This role involves designing and implementing machine learning platforms, coding, code reviews, and automating ML pipelines for large-scale workloads.

Lead the Machine Learning Engineering team, architecting and deploying innovative AI platforms, while ensuring scalability and efficiency across Grab's services.