Software Engineer (Multiple Levels) - Machine Learning Infrastructure, Slack

What you'll do

• Design and build systems to train, serve, and deploy machine learning models at scale.
• Evolve GPU-based inference infrastructure to support high-throughput, latency-sensitive workloads.
• Architect distributed training and data processing systems using platforms like Ray or Airflow.
• Develop robust monitoring and observability for production ML workloads to ensure operational excellence.
• Partner with cross-functional teams to design scalable and secure AI infrastructure solutions.

What we're looking for

• Significant professional experience in software engineering with a focus on infrastructure and backend systems.
• Deep expertise in building and operating distributed systems using Kubernetes and container-based platforms.
• Hands-on experience with modern ML infrastructure stacks like Ray, KubeRay, vLLM for training and inference.
• Experience managing GPU infrastructure at scale for performance optimization and operational efficiency.
• Strong background in data infrastructure technologies such as Airflow, Spark for orchestration and processing.
• Demonstrated ability to drive technical direction and balance short-term goals with long-term architectural vision.
• Excellent written communication skills for asynchronous global team collaboration.