Top AI Jobs in Singapore

Maintain, design, and enhance the Group AI and model inventory system to support AI governance. Implement process improvements, integrate automation, collaborate with model owners, risk, compliance, IT and external reviewers, and drive future-state system implementation and regulatory compliance for Generative and Agentic AI models.

As Senior Growth Director of AI Solutions in APAC, you'll drive AI business growth, nurture client relationships, and lead a sales team.

Lead strategic AI and experience orchestration engagements to accelerate sales adoption of Genesys AI. Advise customers on AI use cases, run workshops and proofs of concept, support deal strategy, enable field programs, create sales materials, and partner cross-functionally to drive measurable CX outcomes.

Lead and scale AI and intelligent automation capabilities across APAC, ensuring adoption, governance, and delivering business value through AI solutions.

Lead product roadmap and define features for an AI API aggregation and routing platform. Write user stories and acceptance criteria, perform competitor analysis, design customer solutions and pricing, deliver POCs, drive developer documentation and SDK examples, operate developer community and growth, and use data to prioritize product iterations and onboarding.

Design and build an AI commerce platform: model routing decision engine, compute pricing and billing, reliability and microservice infrastructure, model evaluation and pricing data pipelines, caching and low-latency performance engineering, frontend and backend full-stack delivery through deployment.

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.

Develop, train, evaluate, and optimize machine learning and deep learning algorithms for audio/video surveillance. Perform data preprocessing and labeling, integrate models into products, research SOTA methods, and document results. Work on detection, feature extraction, tracking, recognition, and deployment/optimization across NPUs/GPUs/DSPs/ARM/CPUs.

Develop, train, evaluate, and optimize ML/DL algorithms and models for audio/video surveillance. Handle data preprocessing and labeling, integrate models into products, research SOTA methods, and document results. Focus includes detection, feature extraction, tracking, recognition, and deployment/optimization on embedded and server platforms.

Own design, build, and productionization of LLM-powered agentic systems for materials R&D: tool orchestration, memory and MCP integration, multi-agent skills, evaluation frameworks, and production reliability/observability. Advise product and platform teams and measure system quality with domain experts.

Join an 18-month graduate/early-career program to build large-scale AI cloud infrastructure: GPU VMs, bare-metal, managed Kubernetes, distributed training and inference, AI Agent platforms, observability, networking, storage, and automation for global AI workloads.

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.

Support embedded ML and biocomputational development for a wearable cardiometabolic platform. Tasks include signal processing, feature extraction, embedded firmware and sensor bring-up, dataset preparation/validation, dashboard visualization, documentation, and collaboration with clinical and research partners under close supervision.

Build, test and support batch and streaming data pipelines and curated datasets on a lakehouse AI data platform. Implement data modelling, partitioning, schema evolution, data quality controls and reconciliation. Collaborate with platform teams and consumers to deliver reliable, scalable data products and reusable tooling; contribute to technical design and mentoring for more senior candidates.

Lead product areas in BJAK's AI Neobank app (insurance, payments, savings, investing, travel). Define user problems, scope, metrics, roadmaps and launch plans. Collaborate with engineering, design, data, operations, compliance and business teams to simplify complex financial products, launch features, monitor performance and iterate using data and user feedback.

Design and scale high-cardinality telemetry for AI datacenters: integrate hardware exporters into Kubernetes, build eBPF diagnostics, create alerting/dashboard pipelines, enable multi-tenant billing metrics, define observability standards, and lead architecture reviews and mentoring.

Design, implement, and operate advanced batch and gang scheduling systems for large-scale AI/HPC clusters. Build admission control, queueing, topology-aware placement, DRA and custom scheduler plugins, and GPU-sharing/multi-tenancy solutions. Integrate scheduling with bare-metal hardware and storage, resolve contention and deadlocks, and mentor engineers to maintain scalable, reliable orchestration stacks.

Design, deploy, and maintain CSI drivers and GPUDirect Storage integrations for high-performance file systems; implement NVMe caching and optimize IOPS/throughput/latency across containerized storage. Collaborate on RDMA/InfiniBand tuning, define Kubernetes storage policies and multi-tenancy isolation, implement monitoring/alerting, and mentor junior engineers.

Lead product direction and execution for major areas of BJAK's AI Neobank app. Define roadmaps, priorities, standards and success metrics across multiple squads. Guide PMs, designers and engineers, manage regulatory and operational constraints, drive launch quality and continuous improvement, and build a fast, outcomes-focused product culture.

Lead end-to-end AI application and productivity initiatives for Chinese-speaking markets. Scope, research, design, test, and roll out AI tools across workflows; build dashboards and tracking; manage cross-functional strategic initiatives; resolve blockers and drive alignment. Hands-on owner who moves fast and embeds repeatable AI best practices.

Drive HPE Private Cloud AI business through partners: develop joint business plans, generate pipeline and orders, align field sales, execute partner enablement and marketing, build executive partner relationships, recruit partners, and ensure partner compliance with HPE requirements.

Lead and grow HPE's HPC and AI sales organization: set quotas and strategy, manage sales teams and partners, drive revenue and market share, build C-level relationships, and develop sales talent and go-to-market execution.

The AI and ML Solution Architect designs and implements AI/ML solutions, collaborates with teams, and improves product performance through advanced algorithms.

This role involves hybrid work, managing sales pipelines, establishing client relationships, and leveraging technical knowledge in HPC and AI to drive sales.

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.