Top Machine Learning Jobs in Singapore

The Cloud Sales Specialist is responsible for revenue accountability, managing customer relationships, preparing sales forecasts, and collaborating with internal teams to enhance customer experience.

6-month internship to design and implement AI-enabled software for telecom Digital Twin platforms. Responsibilities include Python backend and API development, telemetry ingestion, ML model integration, web dashboard visualization, performance optimization, documentation, and final demonstrations to leadership.

Lead product vision, strategy, and roadmap for AI-powered consumer products. Translate user research and analytics into feature decisions, run discovery and experiments, optimize engagement and retention, collaborate with Engineering, AI, Trust & Safety, and customer teams to deliver responsible LLM and personalization-driven experiences.

Lead site-wide Process Analytical Technology (PAT) strategy and deployment across biomanufacturing, delivering real-time analytics, chemometrics, digital twins, closed-loop control, systems integration with MES/DCS/SCADA, regulatory-compliant validation, tech transfer, and capability building to improve yield, robustness, and regulatory readiness.

Lead site-wide Process Analytical Technology (PAT) strategy and deploy real-time analytics, chemometrics, models and digital twins to enable advanced process control, closed-loop automation, and regulatory-compliant validation across ADC biologics manufacturing. Integrate PAT with MES/DCS/SCADA, drive capital projects, tech transfers, capability-building, and performance metrics to improve yield, robustness, and continuous verification.

Conduct research and technical evaluations of AI models, build feasibility studies and proofs-of-concept, mentor and up-skill colleagues, participate in communities of practice, and keep current with AI research to support generative AI programs and internal use-cases.

Design, develop, and deploy machine learning models; preprocess and analyze large datasets; build scalable ML pipelines; fine-tune and monitor models in production; collaborate with cross-functional teams and communicate results to stakeholders.

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.

Conduct research to design and implement simulation and testing environments for drone communication protocols, develop intelligent fuzzing and security evaluation frameworks (including LLM-based agents), perform traffic analysis and anomaly/attack inference, run experiments assessing protocol robustness, automate vulnerability validation, analyze results, and produce technical reports and publications.

Design, implement and maintain simulation and testing environments for drone communication protocols. Build intelligent fuzzing and security evaluation frameworks, traffic-analysis and anomaly-detection methods, and automated validation tools. Conduct adversarial experiments, analyze results, develop LLM-based fuzzing agents, and prepare technical documentation, reports and publications to meet project milestones.

Drive Azure growth for ASEAN high-tech customers by leading technical pre-sales and commercial Azure/AI discussions. Design cloud-native architectures, differentiate Azure versus competitors, map technical solutions to business outcomes, develop migration and commercialization strategies, and work with licensing and compliance to build complex value-based deals.

Develop and validate advanced algorithms, physics-based models, and ML/data-fusion methods for CD-SAXS and OCD metrology. Collaborate with cross-functional teams to prototype, test, and transition research into production-ready solutions; publish papers and file patents. Improve measurement accuracy, robustness, and computational efficiency for semiconductor metrology.

The role involves managing AI and data science projects, engaging stakeholders, and delivering data-driven solutions while leading a team and guiding junior members.

As an AI Product Manager, you will define product roadmaps, run engineering sprints, conduct user testing, and ensure team alignment while translating user pain points into product priorities.

Assist in developing and optimizing AI models, supporting deep learning techniques, and collaborating with engineering teams. Continuous learning and contribution to projects are emphasized.

The Principal Solutions Architect leads technical engagement with strategic customers, focusing on presales, ML workloads, and solution delivery, ensuring successful adoption of Nebius AI cloud solutions.

Lead technical pre-sales for computer vision and AI, design testing solutions, scope customer requirements, and maintain client relationships.

As a Quantitative Research Analyst, you will develop models, conduct complex data analysis, and work with stakeholders to optimize investment strategies.

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.

The AI Governance Officer will ensure ethical AI practices in the AI Lab, supporting project teams throughout the AI SDLC and managing governance compliance.

The VP of Engineering leads application strategy for AI chat products, managing teams and ensuring quality and reliability across platforms.

The Senior Data Scientist will identify fraud patterns, develop machine learning models, collaborate with technical teams, and provide analytical insights to mitigate risks in crypto transactions.

As Senior Product Manager, you'll lead the development of risk products, manage strategies, and enhance risk models to prevent fraud while ensuring customer satisfaction.

The role involves supporting equipment readiness, performing maintenance, troubleshooting equipment, and improving manufacturing productivity while coaching Associate Engineers.

The Product Manager will lead product development, define vision and roadmap, manage engineering activities, and collaborate with various stakeholders.