Top Machine Learning Jobs in Singapore

Build and deploy production machine learning systems for classification, retrieval, ranking, personalization, and evaluation. Develop efficient models and pipelines, improve search relevance and personalization, fine-tune existing models, monitor production performance, and optimize accuracy, latency, cost, and reliability. Collaborate with engineering and product teams to ship measurable improvements for AI-native applications.

Develop and scale AI, machine learning, and advanced analytics solutions for financial crime compliance. Responsibilities include building proof-of-concepts, production analytics pipelines, ML models, and agentic AI workflows; validating model performance and explainability; conducting risk surveillance; investigating anomalies; and communicating analytical insights to stakeholders. The role also supports the compliance innovation roadmap and enterprise adoption of successful AI initiatives.

Own the vision, strategy, roadmap, and lifecycle of a shared lending platform serving multiple products and markets. Define platform architecture principles, APIs, configuration capabilities, and build-versus-buy decisions. Lead real-time credit decisioning, risk and compliance integrations, data aggregation, IFRS9 reporting, and ML-assisted lending capabilities. Coordinate dependencies across lending products and collaborate with Credit Risk, Analytics, Engineering, Compliance, and country business teams.

Leads Cashalo’s 11–12-person backend and mobile engineering team while advising the Philippines GM. Owns ambiguous, cross-market business problems, drives experiments and solutions, and applies proven engineering and product patterns to regional needs. The role requires strong engineering leadership, product judgment, startup experience, AI-enabled workflows, and the ability to engage technically with Staff+ engineers. It is fully remote across Australia, Singapore, or the Philippines, with quarterly travel to the Philippines.

Develop and optimize semiconductor metrology solutions for complex materials and device structures. Work with regional and international wafer fabrication customers on demonstrations, evaluations, product qualification, technical development, troubleshooting, documentation, training, and technical publications. Apply optical modeling, machine learning, statistics, and data analysis to technologies supporting 3D NAND, logic, and DRAM manufacturing.

Supports digital transformation and continuous improvement of chemical production through Smart Operations technologies. Implements, monitors, maintains, and improves digital applications; develops and executes process engineering studies and projects; manages technical changes, MOC activities, documentation, training, and project teams. Collaborates with production, R&D, site management, and global Smart Operations teams to pilot technologies, optimize performance, improve sustainability, and ensure compliance in methionine plant operations.

Participate in a trainee program focused on agentic automation and AI. Design, develop, test, deploy, and maintain RPA and AI-enabled solutions using UiPath, Blue Prism, Xceptor, and Microsoft technologies. Translate business requirements into technical designs, create workflows and integrations, perform testing, document solutions, troubleshoot issues, support deployments, and collaborate with analysts, project managers, engineers, and consultants.

Analyzes sales and distribution performance data to deliver forecasts, reports, dashboards, and actionable insights. Supports channel strategy, compensation analysis, KPI monitoring, and business decision-making. Builds automated reporting and AI-enabled analytics solutions using tools such as Qlik, Power BI, Python, and generative AI. Ensures data accuracy, security, governance, and validation while communicating findings to internal teams and external partners.

Develops automated test equipment solutions for custom semiconductor products from early design through high-volume manufacturing. Responsibilities include creating test plans, validating yield and reliability, developing screening methods, characterizing silicon variation, performing root-cause analysis, optimizing test margins and efficiency, and collaborating with design, DFT, operations, reliability teams, and customers.

Owns ATE production test solutions for custom semiconductor products from early design through high-volume manufacturing. Responsibilities include test architecture, bring-up, test planning, characterization, yield and performance analysis, fault isolation, root-cause analysis, test margin development, and cross-functional collaboration with design, DFT, operations, reliability teams, and customers.

Design technical solutions using Dow Jones data and services, support sales and implementation efforts, guide customers through integrations and proofs of concept, deliver API-focused demonstrations, answer technical questions, and provide product feedback to internal teams. The role requires customer-facing engineering experience, cloud data expertise, programming skills, and strong communication with technical and business stakeholders.

Develop and deploy AI solutions including generative AI copilots, recommendations, RAG, and agentic AI systems. Build predictive and generative machine learning models using structured and unstructured data, apply advanced visualization and storytelling, and collaborate with business and technical teams on cloud, MLOps, and real-time data initiatives.

Leads consultative discovery and solution development for AspenTech customers across Oil & Gas, Chemicals, Power, Mining, and Food & Beverage industries. Partners with sales teams to identify business challenges, demonstrate software capabilities, develop value propositions, create proposals and scopes of work, and support opportunities through solution design and delivery. Requires strong industry, technical, analytical, communication, and consultative expertise, with substantial regional travel across APJ.

Support treasury financial controls, trade surveillance, internal control reviews, audit activities, project implementation, digital transformation, automation, and data analytics initiatives. The intern will use finance and technology skills to monitor controls, investigate trading activity, analyze datasets, and improve processes within Global Markets and Treasury Finance.

Design and deploy advanced process control, automation, and analytics solutions for semiconductor manufacturing. Collaborate with process teams to apply statistical analysis and machine learning, maintain global control applications, develop training, and integrate AI-assisted tools to improve yield, quality, and efficiency.

As a Customer Success Engineer, you will manage enterprise customer relationships, provide technical expertise, and drive integration and adoption of Deepgram's voice AI solutions, ensuring customer success and identifying growth opportunities.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Lead development of advanced dry etch processes for NAND technology, inventing plasma chemistries and equipment capabilities. Use AI/ML, analytics, and automation to accelerate process pathfinding, collaborate with integration and device teams, and drive manufacturability and yield improvements across semiconductor process domains.

Lead and grow a team of diffusion and implant engineers to develop and transfer 3D NAND process modules. Drive process characterization, DOE-driven optimization, process monitoring/control, manufacturability, supplier partnerships, and adoption of data analytics/AI to improve yield, cost, and scalability while supporting pilot ramps and high-volume manufacturing.

Develop production-ready computer vision and multimodal AI systems for interactive applications. Responsibilities include designing algorithms for detection, tracking, segmentation, classification, action recognition, and video understanding; training and optimizing models; managing annotated datasets; evaluating performance; enabling real-time or edge inference; integrating models into production; and collaborating with engineering and data teams. The role also involves research, documentation, testing, and consideration of ethical and regulatory implications.

Supports enterprise data engineering initiatives, including developing and maintaining data pipelines, preparing and validating data, improving data quality, automating manual processes, analyzing and reporting data, and exploring AI-driven solutions. Collaborates with engineering and business teams to gather requirements, translate them into data solutions, conduct testing, document work, and support continuous improvement across enterprise-scale banking data platforms.

Supports semiconductor inspection products through customer demonstrations, product characterization, troubleshooting, test-plan execution, training, documentation, and collaboration with engineering, marketing, and sales teams. Investigates semiconductor manufacturing yield issues, develops inspection solutions, communicates product value, and supports alpha, beta, and ramp activities. The role requires extensive customer interaction and more than 70% travel.

Develops and owns end-to-end machine learning models, from ideation and prototyping through implementation. Responsibilities include building predictive models for credit scoring and recommendation engines, researching model improvements using large datasets, and advancing data science capabilities. Collaborates with analysts and machine learning engineers. Optional experience includes alternate data for credit risk and deep learning or NLP model development.

Develops and owns end-to-end machine learning models, from ideation through implementation. Responsibilities include prototyping credit-scoring and recommendation models, researching improvements using large datasets, and advancing the organization’s data science capabilities. Collaborates closely with analysts and machine learning engineers while applying quantitative, statistical, and business expertise.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.