Top Machine Learning Jobs in George Town

Develop, optimize, and maintain SSD test programs for high-volume manufacturing and NPI. Automate testing with scripts, enhance coverage, debug failures, collaborate with product/equipment teams, monitor metrics, manage test transfers, and mentor junior engineers.

Lead tactical industrial engineering for NAND/SSD manufacturing to optimize operations, align supply and capacity, manage NPI-to-HVM material flow, install processes/automation, investigate material/logistics issues, provide management updates, and coach a team focused on data-driven decisions.

Lead SIP/SSD equipment roadmap and technical development for new and upgraded machines. Improve UPH and yield, standardize automation software and SECS/GEM and database integration with MES, support automation performance and IT collaboration, enable APC/ML/AI-enabled light-off automation, and manage equipment project budgets.

Oversee equipment preventive maintenance, set up and buyoff for form-factor conversions, install and propagate new equipment, troubleshoot major equipment issues, manage spare parts purchasing, train on SOPs and machine operation, lead continuous improvement projects, and follow OSHA safety standards. Use PLC/CTC/C++/Python and control systems for programming and troubleshooting.

Entry-level QA engineer responsible for SSD product quality: monitor OQA/ORT, perform failure analysis and root-cause, define and optimize test flows and automated test programs, produce reliability reports, perform data analysis and automation, and collaborate with R&D, firmware, manufacturing, and stakeholders to resolve quality issues.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Lead engineering projects, automation and digitization, new product qualification, and machine/process reliability. Manage budgets, timelines, root-cause troubleshooting, maintenance strategy, and integration of advanced manufacturing technologies. Mentor and develop engineering team, ensure safety and compliance, and coordinate with regional/global stakeholders to drive productivity and operational excellence.

Develop and support Virtual Factory systems and advanced analytics to optimize semiconductor manufacturing. Implement MES/IIoT integrations, dashboards, SPC/OEE analysis, root-cause investigations, and cross-functional continuous improvement to improve productivity and equipment utilization across global sites.

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, 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.

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.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

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.

Combine supplier quality engineering with data analytics to build ELT pipelines, validate data, create automated Spotfire/Power BI dashboards, perform statistical modeling to monitor and predict manufacturing variances, and drive continuous improvement with supplier and internal teams. Provides rotational weekend support.

Lead a data analytics engineering team to build ELT pipelines, ensure supplier data integrity, implement automated data validation and dashboards (Spotfire/PowerBI), perform statistical modeling to detect and resolve manufacturing variability, and drive continuous improvement in semiconductor foundry, assembly, and test supply chains. Role requires shift support.

Develop and maintain digital twin and machine learning software tools. Build and optimize back-end systems, databases, and data pipelines. Collaborate with engineers and stakeholders to automate workflows, improve data quality, and enhance interpretation of results.

Lead roadmap, planning and delivery of ML/AI products for games. Scope ML efforts, track experiments and metrics, coordinate engineers and game teams, run Agile ceremonies, manage risks and stakeholders, and define evaluation plans for AI features.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

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.

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.

Design, develop, and deploy machine learning models, build and optimize data pipelines/ETL, perform exploratory analysis, ensure data quality, collaborate with engineering/product/business stakeholders, and deliver analytics-driven insights to support business objectives.