Machine Learning Platform Engineer

Overview

Build and operate the infrastructure and platforms powering AI products, covering model training, evaluation, deployment, inference, observability, and continuous improvement.

What you'll do

• Design systems for model training, evaluation, deployment, inference, and experimentation.
• Build and optimise model-serving infrastructure for high-throughput, low-latency workloads.
• Develop pipelines for data preparation, training, evaluation, model release, and continuous improvement.
• Create tooling that helps AI engineers and researchers experiment, evaluate, and ship models faster.
• Build monitoring, tracing, alerting, and observability for AI/ML workloads.
• Identify bottlenecks and improve reliability, scalability, latency, throughput, and cost efficiency.
• Work with AI engineers, researchers, and product teams to deliver production-ready infrastructure.

What you'll need

• Strong software engineering fundamentals and experience building production systems.
• 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.
• Python experience.
• Experience with PyTorch or JAX, cloud infrastructure, and ML/data pipelines.

Details

• Location: Singapore.