ML Engineer (AI)

Location: Remote, Singapore

Company

Building a proactive AI assistant for everyday conversations, errands, organization, and workflows.

What you will do

• Build and own end-to-end ML pipelines covering data, training, evaluation, inference, and deployment.
• Fine-tune and adapt transformer-based models using LoRA, QLoRA, SFT, DPO, and distillation.
• Architect scalable inference systems while balancing latency, cost, and reliability.
• Design data systems for synthetic and real-world training data and implement evaluation for performance, robustness, safety, and bias.
• Own production deployment, including GPU optimization, quantization, memory efficiency, latency reduction, and scaling policies.
• Integrate ML systems with backend, mobile, and desktop products and improve them through real-world usage.

Requirements

• Strong background in deep learning and transformer-based architectures.
• Experience training, fine-tuning, or deploying large-scale ML models in production.
• Proficiency with at least one modern ML framework, such as PyTorch or JAX.
• Experience with distributed training and inference frameworks, such as DeepSpeed, FSDP, Megatron, ZeRO, or Ray.
• Strong software engineering fundamentals and experience building robust, maintainable, production-grade systems.
• Experience with GPU optimization, including memory efficiency, quantization, and mixed precision.

Nice to have

• Experience with vLLM, TensorRT-LLM, FasterTransformer, RLHF pipelines, multimodal or diffusion models, or large-scale data processing.
• Contributions to open-source ML or systems libraries.
• Background in scientific computing, compilers, or GPU kernels.

Culture & Benefits

• Work with a small, high-talent-density, hands-on team.
• Make decisions collectively and ship improvements quickly.
• Operate with autonomy, structured judgment, and a focus on practical product impact.
• Interviews are conducted virtually and/or onsite, with a process of three to four interviews.
• Prompt decisions are expected after technical evaluation.