Top Tech Jobs & Startup Jobs in Singapore

Owns end-to-end machine learning systems across data, training, evaluation, inference, deployment, and monitoring. Builds large-model training and fine-tuning pipelines, evaluation frameworks, high-performance GPU inference systems, and reliable production infrastructure. Partners with research and application engineering to convert model capabilities into measurable product improvements. Provides hands-on technical leadership, makes pragmatic trade-offs, and ensures ML systems are scalable, efficient, safe, reliable, and production-ready.

Lead execution of end-to-end ML systems: data pipelines, training workflows, evaluation, and inference. Translate research into production by fine-tuning large models (LoRA/QLoRA/SFT/DPO/distillation), designing scalable GPU inference, ensuring memory/latency optimization, building evaluation for performance/robustness/safety, and integrating ML into backend and client products while operating under real-world constraints.

Lead production-grade ML systems: build and operate end-to-end ML pipelines, fine-tune large models (LoRA/QLoRA/SFT/DPO/distillation), design scalable inference, ensure GPU optimization, implement evaluation for performance/robustness/safety, and collaborate with product and application teams to ship reliable, low-latency AI features.

Own end-to-end ML systems: data, training, evaluation, inference, and deployment for production-grade LLMs. Build scalable training and inference pipelines, optimize GPU performance and memory, maintain evaluation and safety tooling, and collaborate with application engineers to integrate models into products while balancing latency, cost, and reliability.

Lead strategic execution for the AI Neobank expansion by aligning leadership, building operating rhythms (OKRs, decision tracking), coordinating cross-functional workstreams, preparing leadership/board materials, identifying risks and dependencies, advising trade-offs on people/capital/product/market, and owning high-priority special projects.

Work directly with leadership to drive high-priority, cross-functional initiatives across engineering, product, hiring, operations, and BD. Research markets, build teams and processes, lead projects from planning through execution, and deliver measurable business outcomes in a fast-moving environment.

Support the CEO by turning priorities into execution across product, hiring, licensing, partnerships and market launches. Track OKRs, decisions, blockers, prepare briefs and updates, coordinate cross-functional teams, identify execution gaps, and own urgent cross-departmental problems.

Lead and execute high-priority cross-functional initiatives across engineering, product, hiring, operations, and business development. Build teams, processes, and capabilities; research new markets and products; identify operational problems and implement practical solutions; manage projects end-to-end and deliver measurable business outcomes while communicating with stakeholders.

Own complex technical recruiting searches across AI/ML, software engineering, infrastructure, mobile, and leadership roles. Responsibilities include talent mapping, proactive sourcing and headhunting, technical profile evaluation, hiring-manager partnership, candidate negotiation and closing, and recruiting pipeline improvement. The role requires independently delivering difficult technical hires, advising engineering leaders, and recruiting globally, with a focus on senior and passive candidates.

Lead high-priority technical recruiting searches across AI/ML, engineering, infrastructure, web, and mobile. Build talent maps, source and close senior candidates, assess technical depth, partner with engineering leaders on hiring strategy, coach recruiters, improve pipeline quality, and develop scalable recruiting practices. The role requires hands-on ownership of difficult searches and expertise in technical talent markets.