Software Engineer (Ai)

TL;DR

Software Engineer (AI): Architecting and operating core systems that power AI at Slack with an accent on reliability, security, and self-service capabilities. Focus on solving complex scalability and reliability challenges at the intersection of distributed systems, GPU infrastructure, and modern ML stacks.

Location: Seattle, Austin, Atlanta, Bellevue (USA)

Company

hirify.global's Slack AI mission is to transform how people work by making Slack an AI-powered operating system.

What you will do

• Design, build, and operate systems to train, serve, and deploy machine learning models at scale.
• Evolve GPU backed inference infrastructure to support high throughput, latency sensitive workloads, including large scale model serving.
• Architect and optimize distributed training and data processing systems using platforms such as Ray, Airflow, Spark, or similar technologies.
• Build and maintain Kubernetes based platforms and orchestration layers using tools such as KubeRay, vLLM, and internally developed services.
• Develop robust monitoring, observability, and alerting for production ML workloads to ensure operational excellence.

Requirements

• Significant professional experience in software engineering with a strong focus on infrastructure, backend systems, platform engineering, or MLOps.
• Deep experience building and operating distributed systems, including expert level knowledge of Kubernetes and container based platforms.
• Hands on experience with modern ML infrastructure and serving stacks such as Ray or KubeRay, vLLM, or similar training and inference orchestration frameworks.
• Experience working with GPU infrastructure, including performance optimization and operational management at scale.
• Experience building and operating cloud native systems on public cloud platforms such as AWS, GCP, or Azure, including infrastructure as code.
• Excellent written communication, as well as ability to thrive in an asynchronous and globally distributed infrastructure team.

Culture & Benefits

• Work at the intersection of distributed systems, GPU infrastructure, and modern ML stacks.
• Solve complex scalability and reliability challenges.
• Play a critical part in shaping the long term technical foundations of Slack’s AI capabilities.