Senior ML Platform Engineer: AI Infrastructure & Scale

ActAI; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

ActAI in Singapore is building reliable AI infrastructure to power scalable ML workloads. As an ML Platform Engineer, you will design and operate systems behind the AI stack, from training to deployment, inference, observability, and continuous improvement.

You will collaborate with AI researchers and product engineers to turn evolving model requirements into production-ready platforms, with a focus on high throughput and cost efficiency.

Qualifications

• Strong software engineering and production-grade systems experience.
• Experience building ML infrastructure, platforms, or production machine learning systems.
• Experience with model deployment, inference, evaluation, or data pipelines.
• Strong understanding of distributed systems and system reliability.
• Ability to write clean, maintainable, production-quality code.

Responsibilities

• Build and operate the ML infrastructure powering AI products.
• Design systems for model training, evaluation, deployment, inference, and experimentation.
• Build and optimise model serving and inference infrastructure for high-throughput and low-latency workloads.
• Improve reliability, scalability, latency, and cost efficiency of AI systems.
• Develop reliable pipelines for data preparation, training, evaluation, model release, and continuous improvement.
• Build platforms and tooling that enable AI engineers and researchers to experiment, evaluate, and ship models faster.
• Develop evaluation and benchmarking infrastructure to measure model quality, performance, and regressions.
• Build production observability, monitoring, tracing, and alerting for AI/ML workloads.
• Improve AI systems across reliability, scalability, latency, throughput, and cost.

Skills

Python

Distributed systems

Production systems

Model deployment

Tools

PyTorch

JAX

vLLM

TensorRT-LLM

SGLang

Cloud Infra

Job description

ActAI in Singapore is building reliable AI infrastructure to power scalable ML workloads. As an ML Platform Engineer, you will design and operate systems behind the AI stack, from training to deployment, inference, observability, and continuous improvement.

You will collaborate with AI researchers and product engineers to turn evolving model requirements into production-ready platforms, with a focus on high throughput and cost efficiency.