Software Engineer – ML Infrastructure
People Culture Talent6 hours ago
Base Salary
$150k - $350k/yr
Responsibilities
- Design and build infrastructure for model training and production serving.
- Develop reliable pipelines and shared tools for managing machine learning workloads.
- Improve compute utilization, workload scheduling, and performance across distributed systems.
- Use profiling and monitoring to identify bottlenecks, troubleshoot failures, and guide improvements.
- Automate testing and measurement for consistent assessment of system changes.
- Lead architectural decisions, explain trade-offs, and carry projects from design through deployment and ongoing operation.
- Collaborate with researchers and engineers to turn evolving requirements into maintainable systems.
- Own system maintenance, reliability, and continuous improvement over time.
Requirements
- Substantial software engineering experience with technical ownership at Senior Engineer level or equivalent.
- A track record of personally designing, building, and operating core machine learning infrastructure.
- Hands-on experience with PyTorch, model serving engines, and distributed training frameworks.
- Strong experience with distributed systems and large-scale compute environments, including GPU-based workloads.
- Background in reinforcement learning post-training infrastructure, RLHF, or automated model evaluation pipelines.
- Experience with modern machine learning frameworks and supporting infrastructure.
- Strong systems design, debugging, and performance optimization skills.
- Clear communication skills and the ability to explain contributions, architectural choices, and technical trade-offs.
- Preferred: experience supporting both training infrastructure and production model deployment.
- Preferred: large language model workload experience.
Tech Stack
Categories
About People Culture Talent
We partner with investors, founders, and ambitious teams at pivotal moments of growth, helping them build the people, talent, and leadership infrastructure required to scale with confidence. Our team has helped shape some of the most successful growth stories in technology - including GitHub, Lyft, Notion, and Render - scaling organizations from dozens to thousands of employees and advising companies backed by the world's leading venture investors. We bring deep operating experience, hands-on execution, and a people-first approach to every stage of growth. For more information, please reach out to info@peopleculturetalent.com.