ML Platform Engineer: Build Scalable AI Systems

Cygnify; Singapore; On-site; SGD 150,000 - 190,000; Full time

Benefits offered by this job

Job summary

Cygnify is seeking an ML Platform Engineer to build and operate the infrastructure that powers A1's AI capabilities. You will design and run systems for model training, evaluation, deployment, inference, observability, and continuous improvement, turning research into reliable production services.

You will collaborate with AI engineers, researchers, and product teams to ship scalable platforms, tooling, and data pipelines that enable rapid experimentation, cost efficiency, and robust performance

Qualifications

• Experience building production ML systems.
• Strong background in distributed systems and reliability.
• Hands-on with model deployment and evaluation pipelines.

Responsibilities

• Build and operate ML infra 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 to enable AI engineers and researchers to experiment and ship models faster.
• Develop evaluation and benchmarking infrastructure to measure model quality and regressions.
• Create production observability, monitoring, tracing, and alerting for AI/ML workloads.

Skills

Distributed systems

Production-grade code

ML infrastructure

Model deployment

Python

PyTorch/JAX

Cloud infra

Data pipelines

GPU tooling

Tools

vLLM

SGLang

TensorRT-LLM

VectorDBs

Job description

Cygnify is seeking an ML Platform Engineer to build and operate the infrastructure that powers A1's AI capabilities. You will design and run systems for model training, evaluation, deployment, inference, observability, and continuous improvement, turning research into reliable production services.

You will collaborate with AI engineers, researchers, and product teams to ship scalable platforms, tooling, and data pipelines that enable rapid experimentation, cost efficiency, and robust performance