Top Machine Learning Jobs in Singapore

Conduct interdisciplinary research on generative AI in education, including designing LLM-based dialogue systems, classroom studies, randomized controlled trials, data-analysis pipelines, and learning-process evaluations. Responsibilities include literature reviews, ethics and grant administration, staff supervision, stakeholder coordination, reporting, publications, and dissemination. The role requires translating learning-science principles into AI systems and studying their effects on students’ reasoning, creativity, and argumentation.

Leads and grows Unity’s applied AI research team in Singapore, setting technical direction, developing research roadmaps, and moving machine learning models from prototypes into production. Partners with global product, engineering, and research teams, establishes experimentation and model-quality practices, mentors researchers and engineers, and represents applied research internally and externally. The role focuses on modern machine learning, deep learning, large language models, multimodal models, and applications to games, 3D content, and creative tools.

Serve as the fraud and risk subject matter expert for Stripe Radar, partnering with sales, pre-sales, product, engineering, and customers on complex opportunities. Develop solution strategies, reference architectures, reusable assets, and customer relationships; explain fraud technologies and risk-management patterns; influence product priorities; resolve technical escalations; conduct competitive analysis; and support executive briefings and industry events.

Lead the design, evaluation, deployment, and scaling of predictive Bio-AI models, multi-agent scientific workflows, RAG systems, and LLM applications. Build evaluation frameworks and production controls for model versioning, observability, monitoring, CI/CD, access control, auditability, and human review. Partner with scientists, bioinformaticians, and data engineers to transform scientific workflows into reliable AI capabilities and improve them through experimental feedback.

Develops and deploys advanced analytics and machine learning solutions across operational datasets. Responsibilities include data extraction, cleaning, feature engineering, exploratory analysis, model development, dashboard creation, production monitoring, retraining, documentation, and system integration. The role requires translating analytical findings into actionable insights for engineering and operations partners while working across the full data science lifecycle.

Develops, validates, and improves manufacturing test software for HP products. Responsibilities include test automation, debugging, failure analysis, root-cause investigation, production troubleshooting, test coverage improvement, throughput optimization, documentation, training, and collaboration with product development, quality, factories, and external partners. The role supports new product introduction and sustaining programs while applying software, embedded systems, image processing, and AI/ML technologies.

Supports LaserJet hardware qualification and validation through test automation, engineering data analytics, and AI-enabled workflows. Develops scripts, dashboards, and tools for test execution, data collection, reporting, troubleshooting, and anomaly detection. Prototypes generative AI solutions and agents, collaborates with hardware and test engineers, and documents and validates tools for broader adoption.

Supports large-format printer new product introduction, development, and ink qualification. Develops and executes test plans, performs functional, environmental, and stress testing, and validates product reliability before launch. Collaborates with R&D and manufacturing teams to resolve issues, while analyzing processes and automating repetitive tasks using RPA and machine learning.

Apply mechanical engineering GD&T to precision molding, use statistical methods in production, and support smart manufacturing initiatives. The intern will help develop AI-based anomaly detection and AI agents that advise manufacturing teams on systematic troubleshooting. The role requires collaboration, clear communication, practical problem-solving, and a five- to six-month full-time commitment.

The Staff QA Engineer develops and executes comprehensive software testing strategies across functional, integration, performance, regression, and end-to-end workflows. Responsibilities include building automated test frameworks, integrating tests with Azure DevOps CI/CD pipelines, applying AI-assisted quality engineering, investigating customer escalations, supporting defect resolution, assessing release readiness, and mentoring other SQA engineers. The role collaborates cross-functionally across software development, product management, applications, field service, and customer support teams.

Leads Anthropic’s Applied AI Solutions Architecture organization in Singapore, building and managing the regional team while driving enterprise AI adoption across Singapore, Australia, and New Zealand. The role oversees technical pre-sales, AI strategy, customer workshops, proof-of-concept execution, executive engagement, thought leadership, and cross-functional collaboration. It also establishes regional processes, develops innovative and safe AI solutions, and supports deployments for regulated industries.

Leads Citi’s global Custody sanctions product function, owning strategy, target operating model, architecture, controls, governance, regulatory alignment, and issue resolution. The role directs technology and operational change, represents the business with clients and regulators, develops sanctions training, and builds a high-performing cross-functional team. It requires extensive regulated financial services experience, deep sanctions and custody expertise, and the ability to influence senior stakeholders across a global organization.

Leads APAC equity execution advisory services, supporting algorithmic trading performance analysis, liquidity products, execution platform sales, and customized trading solutions. Partners with clients, sales coverage, product, and quantitative teams to develop analytics, models, Algo Wheel implementations, and product enhancements. Builds institutional client relationships, publishes market content, and drives execution product growth and monetization. Requires extensive equity trading, market microstructure, quantitative analysis, machine learning, and client engagement expertise.

Leads digital transformation initiatives for a manufacturing factory, developing and integrating smart factory systems, dashboards, applications, automated workflows, and Industry 4.0 solutions. Manages projects from requirements through deployment, training, and reporting. Applies Lean and Six Sigma for continuous improvement, supports manufacturing system maintenance, and ensures compliance with IT, validation, safety, quality, security, and regulatory requirements.

Leads cybersecurity governance, risk, compliance, awareness, training, and data protection for a banking environment. Responsibilities include regulatory compliance, security standards, control assessments, audit coordination, risk remediation, security metrics and reporting, phishing exercises, data loss prevention, and investigation of suspicious employee or customer-data activity. The role oversees analytics, machine learning models, visualization, and investigation-platform development while advising senior management and risk committees.

Leads the strategy and delivery of business analytics and insights across the bank. Oversees data scientists, analysts, and reporting specialists; manages analytics initiatives from data processing through deployment; promotes machine learning and AI adoption; establishes data governance; translates findings into executive recommendations; and drives data-informed business, risk, customer experience, and investment decisions.

Build the intelligence layer of a railway data platform by developing end-to-end machine learning solutions for time-series forecasting, anomaly detection, and operational decision intelligence. Responsibilities include data discovery, feature engineering, model deployment, monitoring, scalable data pipelines, automated maintenance alerts, and AI-agent reasoning. The role also involves translating model outputs into dashboard requirements, communicating uncertainty to stakeholders, and collaborating with designers, product managers, and railway engineers.

Lead adoption and scaling of AI across supply chain: define roadmap, prioritize use cases, manage solution lifecycle from pilots to production, establish AI governance and playbooks, improve data readiness, drive stakeholder engagement, build community of practice, and measure business value.

Develop self-supervised, temporal, multimodal, and deep learning models for satellite imagery and geospatial data. Build scalable processing pipelines on GPU and cloud infrastructure, prepare datasets, evaluate models, maintain open-source code, and apply research to coastline change, land subsidence, urban expansion, and vegetation monitoring. Publish papers, present results, and collaborate with the research group.

Develop and apply data analysis, financial reporting, dashboards, automation, and client portal solutions for legal project management in Asia. The role handles complex financial and operational data, creates Excel and Power BI reporting, supports legal service delivery, and provides data-led insights to lawyers, finance teams, technology teams, and senior LPM stakeholders. It also contributes to AI, legal technology, workflow automation, and client-facing collaboration platforms.

Develop a digital twin and analytics framework for semiconductor photolithography equipment. Analyze utilization, throughput, cycle time, and operational data using statistics, machine learning, simulation, and visualization. Build dashboards and predictive models to identify bottlenecks, evaluate optimization scenarios, and improve equipment productivity. Collaborate with engineering teams, document findings, and present recommendations for manufacturing improvement.

Owns regional go-to-market execution and quota-carrying sales for Fortinet’s AI security solutions. Responsibilities include building pipeline, closing complex enterprise deals, engaging executives, delivering product demonstrations, consulting on AI security challenges, training account teams and partners, and evangelizing secure AI deployment, governance, guardrails, runtime protection, and shadow AI prevention.

Lead pre-sales technical execution for regional AI security solutions. Partner with sales teams, train sales engineers and channel partners, conduct technical discovery, architecture reviews, demonstrations, proofs of concept, deployments, and customer training. Manage demo environments and benchmarking, support post-sales handoffs, and build relationships with technical decision-makers. Serve as an AI security evangelist while helping customers secure AI applications, infrastructure, and agentic AI deployments.

Build and improve Document AI models for document extraction, OCR, and layout analysis. Develop scalable training pipelines, work with annotated and synthetic data, apply NLP and computer vision techniques, and optimize models for cloud production. Collaborate with data engineers, DevOps engineers, and architects on deployment and monitoring while translating AI research into product features.

Manage strategic global and regional vendor accounts across multiple markets. Develop joint business plans, financial models, ROI calculators, AI-powered commercial tools, negotiation frameworks, and go-to-market playbooks. Support high-value partner acquisition, vendor investment, and growth initiatives while training local commercial teams. Coordinate with product, marketing, data, and regional stakeholders to scale account-management standards, deploy commercial capabilities, and improve platform and partner outcomes.