Top Machine Learning Jobs in Singapore

Lead regional commercialisation and deployment of AI-powered SME solutions across APAC. Act as APAC subject-matter expert on LLMs and agentic AI, translate customer needs into product requirements, run pilots and go-to-market strategies, and drive adoption through cross-functional collaboration with product, engineering, sales, and partners.

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.

Conducts advanced AI research across foundation models, deep learning, reinforcement learning, computer vision, natural language understanding, and industrial AI. Develops algorithms, prototypes, datasets, ETL pipelines, and machine learning models; evaluates and monitors model performance; collaborates with product and engineering teams on technology transfer and production applications. Publishes research, files patents, documents findings, and advances Microsoft’s research agenda.

Leads complex enterprise customer engagements as a technical authority for Databricks data and AI solutions. Owns architecture, consumption strategy, executive relationships, competitive positioning, migrations, real-time systems, and AI/ML platforms. Orchestrates cross-functional teams, mentors solutions architects, drives platform adoption and revenue growth, and contributes to technical thought leadership through workshops and customer-facing content.

Lead AI risk assessments, identify and mitigate risks in AI projects, audit models and datasets for bias and explainability, implement responsible AI policies, and monitor regulatory developments. The role involves cross-functional collaboration, stakeholder communication, team leadership, coaching, and research across pharmaceutical, clinical, supply chain, and corporate applications.

Supports marketing analytics for OCBC Consumer Banking by exploring data, developing predictive models, managing campaign reporting, defining customer metrics, executing targeted campaigns, and supporting segmentation and product initiatives. Partners with business stakeholders, data engineers, and data scientists to develop analytics solutions, recommendation engines, data pipelines, and automated campaign execution that improve customer acquisition, cross-selling, activation, and marketing effectiveness.

Leads IT business analysis for financial crime compliance and anti-fraud systems, including FCC/KYC name screening, CDD risk scoring, and transaction screening. Gathers requirements, develops functional specifications, designs solutions, estimates costs, manages backlogs, facilitates stakeholder workshops, supports testing and go-live, and monitors solution performance. Collaborates with technology, fraud operations, compliance, engineering, architecture, infrastructure, and security teams using SDLC and Agile methodologies.

Lead FP&A partnership with global commercial teams, own budgeting/forecasting, build GTM KPI/reporting, analyze profitability and unit economics, drive AI-enabled FP&A automation, and mentor junior staff to improve processes and decision-making.

Lead and develop a team of Applied AI Engineers serving enterprise customers across Southeast Asia. Oversee AI solution design, production implementation, reliability, security, evaluation, adoption, and expansion. Coach engineers, handle technical escalations, establish prioritization and coverage models, develop reusable architectures and enablement, and translate customer needs into product feedback. Partner with executives and cross-functional teams while building scalable processes, measuring outcomes, hiring talent, and fostering an inclusive, high-performing organization.

Develop user-facing financial AI and equity research algorithms across query understanding, document processing, entity recognition, event detection, retrieval, ranking, and quality evaluation. Build datasets, labeling systems, benchmarks, and production evaluation frameworks. Apply large language models, NLP, machine learning, reinforcement learning, knowledge graphs, and multimodal methods while collaborating with engineers to deploy and continuously optimize financial data and knowledge systems.

Provides online facilitation for postgraduate business analytics students. Responsibilities include teaching business analytics, predictive modeling, statistical and machine learning techniques, data visualization, and NLP; guiding academic writing and research; conducting online sessions; marking assessments; managing discussion forums; and providing prompt, personalized student support.

Conduct quantitative research and statistical analysis on crypto markets to develop, backtest, and implement automated trading strategies. Work with large and unconventional data sets to build valuation models, refine algorithms, and deploy signals in live trading to drive P&L growth.

Supports technology and market research, emerging technology analysis, new product concepts, requirements gathering, feasibility assessments, user journeys, prototypes, MVPs, and AI-enabled hardware evaluations. The intern researches AI, machine learning, robotics, IoT, sensors, and edge devices; prepares market findings and presentations; and documents testing results, performance, and commercial use cases.

Leads the enterprise strategy, roadmap, operating model, and delivery of data products and Data-as-a-Service capabilities. Oversees data product engineering, governance, security, adoption, monetisation, and value measurement across the bank. Establishes a Data Products Centre of Excellence, builds cross-functional teams, enables self-service data consumption, and partners with senior stakeholders, technology, risk, compliance, and governance teams to deliver scalable, controlled, and commercially valuable data capabilities.

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.

Conduct research on efficient, scalable systems for multi-agent AI and HPC workflows. Responsibilities include workload analysis, system prototyping, benchmarking, performance optimization, and experimental validation on supercomputing platforms. The role involves collaborating with faculty and domain scientists, developing innovative technical solutions, and contributing to research papers, reports, presentations, and conference or journal submissions.

Design and build the foundational data layer, pipelines, and integrations for a manufacturing data platform. Develop backend services, APIs, and user-facing applications; implement data quality, monitoring, resilience, and audit capabilities; produce documentation, runbooks, and QA for production readiness; collaborate with operations and stakeholders to iterate on UI/UX and business logic.

The Senior Solution Consultant supports complex enterprise sales by conducting technical discovery, workshops, demos, RFx responses, solution design, and architecture documentation. The role maps customer business and technical needs to Genesys solutions, develops reusable integrations and infrastructure solutions, and presents business value to executive stakeholders. Responsibilities include leading presales teams, creating sizing calculations and diagrams, advising on CCaaS and AI technologies, and collaborating with sales, partners, architects, engineers, and services teams.

Lead product strategy for real-time and post-transaction monitoring across payments. Own rules, alerting, workflows, investigator tooling, client-specific controls, and AI-driven detection, partnering with Risk, Compliance, Data, and Engineering to reduce fraud while preserving customer experience and operational efficiency.

Lead product strategy and execution for real-time and post-transaction monitoring across payments. Own rule design, alert optimisation, investigator tooling, client-specific controls, and scalable detection infrastructure. Partner with Risk, Compliance, Operations, Data, and Engineering to reduce fraud, leverage AI/analytics, automate workflows, and ensure AML/regulatory alignment while preserving customer experience.

Lead product strategy for real-time and post-transaction payment monitoring. Own rule design, alert optimisation, investigator tooling, client-specific controls, and AI-driven detection improvements while partnering with Risk, Compliance, Data, Operations, and Engineering to reduce fraud and operational overhead and ensure regulatory alignment.

Develop analytics, operations-research and machine-learning solutions and web applications to improve semiconductor manufacturing efficiency and scheduling. Manage requirements, stakeholders, and delivery; collaborate across teams; integrate AI-assisted tools; and support continuous improvement in capacity, cycle-time, and scheduling optimization.

Designs and develops content governance platforms, anti-abuse tools, rule engines, and scalable governance pipelines. Integrates recommendation systems, implements content takedown policies, and builds capabilities for content review, risk detection, policy enforcement, and effectiveness analysis. The role addresses spam, fraud, traffic diversion, low-quality content, and black- or gray-market activity while collaborating with product, operations, algorithm, and business teams.

Design and implement AI-powered productivity solutions, research and evaluate emerging AI technologies, and translate theoretical AI into scalable business applications. Collaborate with executives, business leaders, and technical teams globally while communicating complex technical concepts to nontechnical stakeholders.

Conduct research on AI-based process monitoring for laser-based metal additive manufacturing. Responsibilities include collecting thermal data, developing data-efficient AI models, detecting anomalies and material defects, implementing real-time layer-wise monitoring, optimizing process parameters, supporting energy-system collaborations, maintaining laboratory resources, documenting findings, mentoring students, and assisting with research proposals and publications.