Top Machine Learning Jobs in Singapore

Leads global AI-first MarTech engineering strategy, architecture, governance, compliance, and delivery. Oversees scalable digital platforms, public-facing properties, GenAI applications, R&D, proof-of-concepts, and automated compliance capabilities. Builds and mentors a global team of engineering and AI professionals, manages vendors, and partners with marketing, business, cloud, security, privacy, infrastructure, and legal stakeholders to deliver secure, high-performance digital experiences.

Deploy production computer vision systems for new customers, including data pipelines, model optimization, edge hardware configuration, infrastructure integration, troubleshooting, and knowledge transfer. Work closely with customer engineering and operations teams in physical environments, identify deployment risks, document architectures, and provide product feedback. The role requires strong Python skills, production ML deployment experience, edge computing knowledge, and travel of approximately 40–50%.

Owns the strategy, requirements, evaluation, and quality of AI-powered products. Partners closely with ML, backend, and client engineering teams to define system behavior, assess model performance, manage trade-offs across quality, latency, cost, reliability, safety, and UX, and establish feedback loops. The role requires strong technical judgment, hands-on experience with AI or LLM products, and the ability to turn ambiguous problems into measurable requirements and executable plans.

Expression of interest for future research scientist or research engineer opportunities at Neo Research. The organization seeks candidates working in model evaluations, AI alignment, interpretability, machine learning, large language model engineering, agentic systems, or related fields applicable to frontier AI safety. Prior AI safety experience is not required. Reading and writing Mandarin is a plus.

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.

Lead hands-on development of generative AI products grounded in enterprise knowledge. Design LLM, embedding, multimodal, fine-tuning, retrieval-augmented, and agentic solutions; rapidly prototype and evaluate GenAI applications; and scale successful experiments into production systems. Provide technical direction to a tiger team, mentor engineers and scientists, influence retrieval and serving architecture, shape innovation strategy, and promote responsible AI, groundedness, and data quality.

Lead the technical strategy and project execution for CuspAI in Singapore, managing local teams and translating commercial needs into technical solutions. Drive growth and partnerships while ensuring alignment with global strategies.

Develops market requirements, product strategies, marketing plans, positioning, pricing, and lifecycle plans for semiconductor chemical metrology and process-control products. Conducts market and competitive research, identifies customer needs, supports new product definition, and collaborates with engineering, manufacturing, sales, and regional teams. Owns selected accounts and regions, supports pre- and post-sales initiatives, presents to customers, and drives product penetration and adoption strategies. Travel is required 30–40% of the time.

Develops and deploys AI, machine learning, GenAI, automation, and analytics solutions for Group Risk Management. Partners with business, risk, data engineering, data science, and technology teams to translate business needs into measurable outcomes. Guides model selection, GenAI cost estimation, benefit realization, responsible AI, data governance, and regulatory compliance while promoting an AI-enabled culture.

Lead scientific delivery of partner materials-discovery projects from scoping through results. Apply simulation, machine learning, data-driven optimization, and experimental methods to design discovery campaigns and validate outcomes. Translate between computational and experimental teams, develop reliable automated workflows, maintain high-quality data pipelines, and communicate technical findings to partners. The role also involves project leadership, partner-lab collaboration, technical reporting, and contributing to platform and capability development.

Leads NTU Singapore’s technology audit capability, including risk-based audit planning, cybersecurity and IT control assessments, cloud and enterprise systems audits, data governance, digital transformation, and AI initiative reviews. The role presents technology risks to senior leadership and the Audit & Risk Committee, develops audit methodologies and analytics, coaches auditors, manages external specialists, and evaluates controls across research and university technology environments.

Develop and deploy AI-driven solutions, including generative AI copilots, recommendation systems, RAG, and agentic AI. Build predictive and generative models using large-scale structured and unstructured data. Apply advanced visualization and storytelling, collaborate with business stakeholders, and use cloud, MLOps, and real-time data platforms to solve banking challenges.

Build and maintain customer lifetime value, churn, conversion, clustering, classification, and sentiment analysis models across APAC markets. Partner with commercial, marketing, and finance teams to translate business questions into analytical solutions, present insights to non-technical stakeholders, and manage the full data science lifecycle from problem framing and data extraction through deployment and monitoring.

Develop and deploy predictive models, analyze large datasets, identify trends, create data visualizations, and provide insights for strategic business decisions. Collaborate with stakeholders and cross-functional teams to understand business needs, communicate findings, and develop data-driven solutions while staying current with data science and machine learning advancements.

Leads regional retail marketing strategy and marketing technology across Singapore, Malaysia, Thailand, Indonesia, and Vietnam. Drives digital and performance marketing, AI and advanced technology adoption, brand alignment, governance, campaign effectiveness, budget controls, process improvement, and agency performance. Acts as the marketing technology subject matter expert, partnering with internal stakeholders, country marketing teams, media agencies, and digital functions to improve marketing productivity, efficiency, and business outcomes.

Leads vehicle data product strategy across Southeast Asia, owning portfolio roadmaps, prioritization, customer discovery, reporting frameworks, and execution from discovery through launch. Partners with designers, developers, data scientists, technical project managers, customers, and senior leaders to align product initiatives with business growth. Uses engagement metrics, product KPIs, customer feedback, and strategic analysis to improve products, validate solutions, communicate product vision, and mentor product managers.

Supports APAC service growth initiatives through data analysis, machine learning models, revenue forecasting, capacity planning, and Power BI dashboard development. Performs SQL and Power Query ETL, data modeling, visualization, and reporting while contributing to program management, cadence planning, impact tracking, and problem solving.

Supports APAC service growth initiatives by analyzing business operations, regional trends, revenue forecasts, and capacity planning. Builds machine learning models, Power BI dashboards, DAX measures, and ETL workflows using SQL and Power Query. Translates business requirements into visualizations and reports, ensures data accuracy, communicates insights, and assists with program management planning and problem-solving.

Supports manufacturing process development, new product introduction, process documentation, continuous improvement, prototype validation, issue resolution, and automation projects involving robotics and PLC applications. The intern evaluates tooling, costs, time standards, drawings, and process requirements while helping improve productivity, quality, efficiency, and manufacturability in a high-precision manufacturing environment.

Install, align, calibrate, troubleshoot, diagnose, and repair complex semiconductor capital equipment at customer sites worldwide. Provide post-installation support, coordinate with customers and field service engineers to minimize downtime, verify equipment performance, and document service activities and recurring issues. The role requires independent work, strong communication, adaptability, and more than 80% travel.

Develop and deploy applied AI/ML solutions for intelligent transportation, including computer vision, generative AI, agentic AI, data pipelines, and machine learning algorithms. Collaborate with technical and business stakeholders, iteratively refine products with users, evaluate emerging technologies, and establish engineering best practices. The role also involves cloud solution deployment, DevOps practices, testing, version control, and knowledge sharing.

Develops and maintains robust software for semiconductor metrology systems, translates customer needs into requirements, improves software performance, resolves technical issues, and recommends enhancements. The role requires advanced software engineering, AI and machine learning experience, local or edge LLM deployment knowledge, scientific computing, algorithms, numerical methods, and analytical problem-solving.

Leads Citi’s global Custody sanctions product function, owning product strategy, operating model, architecture, governance, controls, regulatory alignment, and issue resolution. Partners across Technology, Operations, and risk teams to deliver sanctions capabilities, represents the business with clients and regulators, develops training, and manages a high-performing global team.

Design production-ready AI/ML architecture blueprints, open-source AI Quickstarts, and reference codebases for enterprise customers. Collaborate with technology partners to validate integrations, build benchmarking and evaluation systems, and incorporate telemetry for latency, throughput, cost, and model quality. Apply secure, privacy-preserving, regulated deployment practices, including isolated networks, data residency, and local inference. Work hands-on with Python, PyTorch, Kubernetes, MLOps, generative AI, model-serving runtimes, and heterogeneous hardware optimization.