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# Software Engineer, AI Infra

- **Company:** Robinhood
- **Location:** Menlo Park, CA, United States
- **Experience:** Expert
- **Salary:** $196,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Distributed Systems, Machine Learning, Open Source Technology, Performance Tuning, Software Engineering, Feature Store, Large Language Models, Backend, Information Technology, Low Latency, Machine Learning Operations
- **Published:** October 31, 2026
- **Apply:** https://www.themuse.com/jobs/robinhood/senior-software-engineer-ai-infra

## About the Role

* Strong software engineering experience with a focus on infrastructure, distributed systems, or large-scale backend platforms.
 * Hands-on experience designing, building, and operating distributed systems in production, with a strong understanding of scalability, reliability, and system performance.
 * Experience solving complex infrastructure challenges, including latency optimization, resource utilization, and production system reliability.
 * Strong software development and system design skills, with the ability to take ownership of complex technical problems from design through production.
 * Experience working with infrastructure technologies and tools in production environments, with an understanding of how to build and operate reliable systems at scale.
 * Ability to work independently, navigate ambiguity, and contribute to foundational engineering projects within a small, growing team.
 * Interest in machine learning and AI infrastructure, with a willingness to learn and work across both traditional infrastructure and emerging AI technologies.
 * Bonus: Experience with ML infrastructure, model training or serving, GPU workload scheduling, LLM gateways, or open-source infrastructure technologies.

## Description

* Design, build, and scale the infrastructure powering machine learning and AI across Robinhood, including feature stores, training pipelines, model serving, inference, and observability.
 * Build and optimize distributed systems that support large-scale ML/AI workloads, with a focus on performance, reliability, scalability, and latency.
 * Improve GPU utilization and efficiency by developing scheduling solutions for training and inference workloads.
 * Help evolve Robinhood's LLM gateway, including intelligent model routing, query and prompt understanding, and context optimization.
 * Support infrastructure for serving open-weight and fine-tuned models, enabling reliable access to AI capabilities across the company.
 * Partner with engineering teams across Robinhood to understand their infrastructure needs and build scalable, reusable solutions.
 * Own the operational health of critical infrastructure, including monitoring, troubleshooting, performance optimization, and participation in an on-call rotation.