Top Machine Learning Jobs in Singapore

The Senior Engineer will enhance production efficiency, manage semiconductor equipment processes, and lead improvements in memory product development through engineering methods and collaboration.

Develop, test, deploy, and maintain AI-powered applications, backend services, APIs, integrations, and automation. Implement LLM, RAG, prompt engineering, model API, and agentic workflow capabilities. Support experimentation, troubleshoot defects, monitor services, improve reliability and performance, and follow security, privacy, responsible AI, and change-control requirements. Collaborate with engineers, product managers, designers, governance teams, and global stakeholders while contributing maintainable code, documentation, testing, and technical improvements.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Develop and maintain high-performance risk metrics engines and workflows for counterparty credit risk. Build scalable, resilient backend systems and data/calculation pipelines, integrate AI and cloud technologies, write production-grade code and tests, and collaborate with quantitative engineers and product managers to implement next-generation architecture.

Conduct research in embodied AI and robotic manipulation by developing perception and control algorithms, integrating multimodal AI with robotic platforms, and testing systems in simulation and real-world environments. The role involves working with robotic arms and mobile robots, supporting research publications, collaborating with academic and industry partners, and maintaining laboratory equipment.

Own product initiative delivery from kickoff through release, coordinating Product, Engineering, Data, and Solutions. Track dependencies, risks, blockers, scope changes, timelines, testing, handoffs, and launch readiness. Maintain accurate project status and documentation while ensuring execution remains aligned with product intent. This hands-on role requires technical fluency, cross-functional communication, strong ownership, and daily overlap with an Asia-based technology team.

Develop and deploy advanced machine learning models across asset classes, focusing on deep learning, sequence/time-series modeling, NLP/LLMs, pre-training, fine-tuning, and reinforcement learning. Design and optimize models for performance, scalability, and robustness to model price formation, market behavior, and risk while collaborating with researchers, engineers, and traders.

Own an AI finance product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, launch, and regulatory readiness. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Apply AI with rigorous evaluation, safeguards, human oversight, and reliability controls. Coordinate engineering, design, compliance, operations, treasury, and finance while managing financial rails, third-party dependencies, and trade-offs across correctness, speed, cost, regulation, and user experience.

Own an AI investing product vertical end to end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reliability, security, and scalability. Embed KYC, transaction monitoring, privacy, licensing, and other regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Conduct numerical modelling and optimal control strategy development for building energy, energy storage, and fire systems. Collect, standardize, and integrate experimental and simulation data; apply AI and machine learning to accelerate simulations; validate models and algorithms; publish research papers and pursue patents. The role also requires progress reporting, independent solution development, and collaboration under strict timelines.

The CE PYE FA Engineer conducts fault isolation and failure analysis, collaborates with engineering teams, and develops innovative techniques to improve defect resolution.

The role involves electrical failure analysis, fault isolation, collaboration with product engineering, and process improvement strategies.

Lead the architecture and integration of scalable Health AI solutions across Asia. Design secure, reusable enterprise patterns for Generative AI, RAG, agentic workflows, data pipelines, and Azure-based platforms. Partner with data science, engineering, business, security, and governance teams to translate health priorities into production-ready solutions. Establish standards, guide implementation from prototype to scale, influence roadmaps, mentor teams, and ensure measurable business impact, governance, monitoring, and risk controls.

Conduct research and experiments for game AI bots using reinforcement learning and generative AI. Support scalable AI services, optimize deployed models, evaluate performance, and troubleshoot bugs. Explore new approaches to improve model effectiveness while collaborating with the data and AI team.

Designs production-ready AI/ML architecture blueprints and open-source Quickstarts for enterprise customers. Builds Python-based solutions using deep learning, cloud-native platforms, MLOps, model serving, evaluation harnesses, telemetry, and secure regulated deployment patterns. Collaborates with engineering partners to validate integrations, optimize performance across heterogeneous hardware, and address privacy, compliance, data residency, and network isolation requirements. The role emphasizes autonomous technical delivery without people management or formal project coordination.

Conduct research on earthquake hazards, fault geometry, and rheology; generate rapid disaster maps using remote sensing and space geodesy; improve InSAR deformation and coherence time-series analysis with machine learning; analyze geospatial and geodetic datasets; and collaborate with multidisciplinary teams to translate findings into operational applications and publications.

Develop an AI-enhanced Power BI dashboard integrating supplier, subtier, forecast, and capacity data. Build predictive models to identify supply chain delivery gaps, single-point-of-failure risks, capacity constraints, and geographical or sourcing dependencies. Analyze demand trends and create early-warning indicators and scenario analyses that support supplier account management, proactive risk mitigation, and resilient supply chain planning.

A 12-month graduate programme offering technology and AI/data science tracks. Associates may work in application development, DevOps, cybersecurity, data engineering, AI/ML, infrastructure, cloud, or advanced analytics. Responsibilities may include building GenAI and agentic AI solutions, developing ML models, applying MLOps, governing responsible AI, and collaborating with technical and business teams.

Supports computational chemistry and AI/ML projects by modeling reaction pathways, molecular behavior, catalytic mechanisms, and chemical properties. Prepares datasets, runs DFT and simulation calculations, evaluates reaction intermediates and transition states, and develops Python-based regression, classification, and neural network models. Cleans data, engineers features, evaluates models, analyzes outputs, documents findings, and collaborates with chemists to translate results into material and molecule design insights.

The role involves developing advanced thin film deposition processes, conducting experiments for process improvement, collaborating with teams, and mentoring junior engineers.

The role involves fault isolation and failure analysis support, operating equipment for electrical defect localization, collaborating with teams for defect resolution, and leading a team of technicians.

Lead implementation and enhancement of AML/CFT transaction monitoring systems across the Group. Act as SME for TM solutions, gather and document requirements, drive end-to-end projects, coordinate UAT, optimize alerting via statistical tuning, deploy analytics/AI/ML and RPA, manage stakeholders, provide training, and ensure regulatory and audit readiness.

Lead operational excellence for AI applications in a banking environment by managing lifecycle, evaluating performance, and ensuring compliance. Collaborate with teams to enhance agent-driven solutions and optimize prompt tuning for generative models.

Lead enterprise data product and Data-as-a-Service strategy, delivery, operationalization, governance, and adoption within a regulated banking environment. Build reusable, governed data products supporting analytics, AI, reporting, and business decision-making. Establish operating models, metadata and lineage standards, quality controls, self-service consumption channels, and Centre of Excellence practices. Partner with senior stakeholders, engineering, technology, governance, risk, and business teams to prioritize use cases, manage delivery, enable AI context, and track measurable value.

Lead regional AFC/AML analytics capability: design, build, validate and deploy AML/fraud detection models; guide country analytics teams; ensure model governance, data suitability, and production readiness across stakeholders and regions.