Software Engineer (Machine Learning Infrastructure)

TL;DR

Software Engineer (ML Infrastructure): Design, build, and operate foundational systems for large-scale machine learning training, serving, and deployment at Slack with an accent on distributed systems, GPU infrastructure, and modern ML stacks. Focus on architecting scalable model inference, optimizing high-throughput workloads, and ensuring reliability for AI-driven capabilities across the company.

Location: Washington - Seattle, Texas - Austin, Georgia - Atlanta, Washington - Bellevue

Company

Slack AI, part of hirify.global, builds AI-powered features to transform workflows by unlocking knowledge and reducing noise in Slack.

What you will do

• Design, build, and operate systems for training, serving, and deploying ML models at scale with focus on reliability and performance
• Evolve GPU-backed inference infrastructure for high-throughput, low-latency workloads including large-scale model serving
• Architect distributed training and data processing using Ray, Airflow, Spark, or similar
• Build Kubernetes-based platforms with KubeRay, vLLM, and internal services
• Develop monitoring, observability, and alerting for production ML workloads
• Partner with AI Platform, ML modeling, security, and product teams on infrastructure for evolving AI use cases
• Provide technical leadership through design reviews, mentorship, and architecture direction

Requirements

• Significant experience in software engineering focused on infrastructure, backend, platform engineering, or MLOps
• Deep expertise in distributed systems and Kubernetes/container platforms
• Hands-on with ML infrastructure stacks like Ray, KubeRay, vLLM
• Experience with GPU infrastructure optimization and management at scale
• Strong knowledge of data orchestration like Airflow, Spark
• Cloud-native systems on AWS, GCP, or Azure with infrastructure as code
• Ability to drive technical direction balancing short- and long-term goals
• Excellent written communication for asynchronous, global team
• Related technical degree

Culture & Benefits

• Work in a globally distributed infrastructure team
• Thrive in asynchronous communication environment
• Contribute to engineering blog posts and thought leadership