Top Machine Learning Jobs in Singapore

The Responsible AI Specialist will develop AI governance standards, conduct risk assessments, engage stakeholders, and promote ethical AI practices across UOB.

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.

As a Principal Engineer, you'll lead CMP process development, optimization, and sustainability, while collaborating with teams to enhance performance and drive innovation in semiconductor fabrication.

Design, develop and roll out geospatial AI-centric MVPs and digital products. Work full-stack on frontend and backend, implement and fine-tune ML/GenAI/LLM models, use cloud and DevSecOps practices, collaborate with stakeholders in cross-functional teams.

Lead the development of AI tools that optimize the software development lifecycle, mentor teams, and implement scalable ML systems.

As a Senior Data Scientist, you'll develop scalable machine learning algorithms focused on search and ranking, process datasets, deploy models, and run A/B tests.

The Regional Business Actuary will drive growth in GrabInsure by managing product pricing, data analysis, risk assessment, and partnerships while ensuring compliance and reporting.

As a Principal Machine Learning Engineer, you will lead a team, develop scalable machine learning solutions, and enhance ad serving efficiency for Grab's ads business.

The AI Product Owner will drive AI integration into the Razer Gold Digital Wallet, optimizing operations and enhancing user experience through innovative features and data-driven insights across teams.

The Head of Data Science will lead the data science team across Southeast Asia, focusing on credit risk model development, strategic collaboration, and shaping the machine learning roadmap.

Lead the development of regional marketing strategy and digital transformation for group retail, ensuring governance and efficient processes across multiple markets.

As a Data Scientist, you will translate business problems into data analytics solutions, manage the ML lifecycle, and improve driver incentives through statistical analysis.

The Business Development Manager at HPE drives growth through strategic partnerships with NVIDIA, focusing on expanding market presence and supporting sales enablement for AI solutions.

Design, build, and productionize GenAI and ML solutions for semiconductor engineering: large-scale data pipelines, LLM/RAG and agentic workflows, model training/inference, analytics, deployment, monitoring, and cross-functional collaboration to improve quality, cost, and engineering productivity.

The Principal Machine Learning Engineer will architect and execute ML solutions, optimize training efficiency, and develop autonomous AI agents for Micron Technology's manufacturing processes.

As a Machine Learning Engineer Intern, you will build data pipelines, develop models, and collaborate on data-driven solutions in manufacturing. Gain experience with cloud platforms and MLOps.

The role involves leading the development of data and analytics solutions, focusing on machine learning and NLP to improve financial decision-making.

As a Principal AI Engineer, you will lead the architecture and deployment of large-scale conversational chatbot systems, optimizing their performance for enterprise and consumer use cases.

Lead the development of advanced perception algorithms for autonomous vehicles, optimize real-time performance, mentor junior engineers, and integrate systems.

The Data Science Intern analyzes large datasets, uses machine learning and analytics to solve gaming challenges, and collaborates with teams to drive business strategies.

The role involves maintaining equipment readiness, performing preventive maintenance, troubleshooting equipment, and supporting safety practices in an engineering environment.

Lead APAC AI innovation for the COE: run workshops, mentor teams, prototype and build LLM/automation solutions (including Google Apps Script), industrialize experiments into deployed, billable tools, and scale an internal innovation community.

Design, build, deploy, and maintain applied AI solutions (computer vision, generative and agentic AI). Develop and optimize ML algorithms, implement scalable data pipelines, collaborate with cross-functional teams, engage users iteratively, and evaluate emerging technologies to deliver prototypes and MVPs improving transport experiences.

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.