Machine Learning Platform Engineer (IT Engineer/ WFH)

About Company

Our client is one of Southeast Asia’s largest tech aggregators, building the world’s next generation of AI-native productivity applications.

Job Description

• Build and operate the ML infrastructure and platforms powering A1’s AI products
• Design systems for model training, evaluation, deployment, inference, and experimentation
• Build and optimize 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
• Identify bottlenecks across the ML stack and continuously improve system performance
• Work closely with AI engineers, researchers, and product teams to turn evolving model requirements into production-ready infrastructure
• Other ad hoc duties as assigned by the company

Job Requirements

• 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
• Comfortable working in ambiguous, fast-moving environments
• Bias toward ownership, experimentation, and continuous improvement
• Tech stack: Python, PyTorch / JAX, LLM and ML serving infrastructure such as vLLM, SGLang, or TensorRT-LLM, Cloud infrastructure
• Preferably experienced in Distributed systems, ML/data pipelines and workflow orchestration, GPU infrastructure and performance tooling, Vector databases and retrieval infrastructure

Compensation

• Remote job/ Fully Working from Home (WFH)
• Working hours: Office hours (depending to job location)