Dada Consultants Hiring! Full Time AI Infrastructure Engineers (GPU Compute, Distributed Training, LLM Inference - AI Systems, Multiple Openings) in - Ricebowl

My Client

We are supporting an ambitious AI technology company that is expanding its core AI Infrastructure & Systems Engineering team in Singapore.

The team is building the foundational infrastructure powering next-generation AI models, large-scale training and inference, and advanced AI research. Their work spans distributed computing, GPU acceleration, model runtimes, research automation, and production reliability.

Multiple opportunities are available across different engineering domains. Candidates are expected to have deep expertise in one of the following areas.

Key Engineering Areas

• GPU Compute & Cluster Infrastructure – GPU resource management, Kubernetes-based scheduling, workload orchestration, cluster performance, GPU health monitoring, NCCL and high-performance networking.
• Distributed Training Infrastructure – Large-scale LLM training systems, PyTorch Distributed, Megatron-Core, model parallelism (TP/PP/EP), checkpointing, fault recovery and training efficiency.
• LLM Inference Infrastructure – High-performance model serving, vLLM/SGLang, KV-cache management, continuous batching, speculative decoding, multi-node inference and throughput/latency optimization.
• AI Kernel & Performance Engineering – CUDA/Triton, GPU kernel development, Attention/MoE optimization, quantization, memory efficiency and low-level performance tuning.
• AI Data Infrastructure – Large-scale data processing with Ray/Spark, distributed storage, data pipelines, high-throughput I/O and data infrastructure supporting model training.
• RL Systems & AI Research Infrastructure – Reinforcement learning execution systems, distributed rollouts, training orchestration, research experiment automation and model evaluation pipelines.
• Cloud Platform & Site Reliability Engineering – Kubernetes/Linux, infrastructure automation, observability, incident management, disaster recovery, platform security and production reliability.

Job Requirements

• Bachelor's degree or above in Computer Science, Engineering, or a related technical field.
• Solid programming skills in Python, Go, or similar languages, depending on the technical direction.
• Experience designing, developing, optimizing, or maintaining complex distributed systems, AI/ML infrastructure, or production-grade platforms.
• Strong understanding of system architecture, performance optimization, scalability, and reliability.
• Excellent problem-solving skills and the ability to investigate complex technical issues at the system level.
• Hands-on engineering mindset, with the ability to take ownership of challenging technical problems.

Nice to Have

• Experience with large-scale AI training/inference platforms, GPU clusters, hyperscale cloud infrastructure, or HPC environments.
• Hands-on exposure to Kubernetes, CUDA/Triton, NCCL, RDMA, Ray/Spark, PyTorch Distributed, Megatron-Core, vLLM or SGLang.
• Experience building core infrastructure at leading AI companies, cloud providers, research labs, or large-scale technology platforms.
• Contributions to open-source AI infrastructure, distributed systems, or high-performance computing projects.

What They Offer

• Opportunity to work at the forefront of AI innovation, building foundational infrastructure that directly powers next-generation AI models and cutting-edge research.
• Strong technical ownership across large-scale AI training, inference, and distributed computing systems, with the opportunity to solve complex engineering challenges.
• Highly competitive compensation and close collaboration with talented AI researchers and experienced systems engineers.

About Us

Dada Consultants was established in 2017, with the commitment of providing the best recruitment services in Singapore. We are comprised of a dynamic head-hunting team dedicated to sourcing for highly competent professionals in IT industry. We provide enterprises with customized talent solutions, and bring talents to career advancement.

If it sounds like your next move, please don’t hesitate to apply. Kindly note that only shortlisted candidates will be contacted. Appreciate your understanding. Data provided is for recruitment purposes only.

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EA Registration Number: R26160730

Business Registration Number: 201735941W. Licence Number: 18S9037