Machine Learning Platform Engineer

Stack

Responsibilities

• ▹Build and operate the ML infrastructure and platforms powering AI products
• ▹Design systems for model training, evaluation, deployment, inference, and experimentation
• ▹Build and optimise model serving and inference infrastructure for high-throughput, low-latency workloads
• ▹Improve reliability, scalability, latency, and cost efficiency of AI systems
• ▹Develop reliable pipelines for data preparation, training, evaluation, and model release
• ▹Develop evaluation and benchmarking infrastructure to measure model quality and performance
• ▹Build production observability, monitoring, tracing, and alerting for AI/ML workloads
• ▹Work closely with AI engineers, researchers, and product teams

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

Nice to have

• ▹Python
• ▹PyTorch/JAX
• ▹LLM and ML serving infrastructure (vLLM, SGLang, TensorRT-LLM)
• ▹Cloud infrastructure
• ▹GPU infrastructure and performance tooling
• ▹Vector databases and retrieval infrastructure

Soft skills

About the company

A1's mission is to build a proactive smart assistant for everyday users, focused on high reliability for long-running workflows, persistent context, and real-world task completion.