Software Engineer – ML Infrastructure

• Design and build infrastructure for model training and production serving.
• Develop reliable pipelines and shared tools that help teams run and manage 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 to help teams assess changes consistently.
• Lead architectural decisions, explain trade-offs, and carry projects from initial design through deployment and ongoing operation.
• Collaborate with researchers and engineering teams to turn evolving requirements into maintainable systems.

• 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.
• Solid background in reinforcement learning (RL) post-training infrastructure, RLHF, or automated model evaluation pipelines
• Practical experience with modern machine learning frameworks and their supporting infrastructure.
• Strong systems design, debugging, and performance optimization skills.
• Clear, concise communication and the ability to explain your contributions, architectural choices, and technical trade-offs.
• Experience owning systems over time, including maintenance, reliability, and improvements as requirements evolve.

• Experience supporting both training infrastructure and production model deployment.
• Experience with large language model workloads is a plus, but not required. Infrastructure experience with other types of machine learning models is equally relevant.

Note: We are recruiting on behalf of our valued client. This opportunity is for a position with their organization, not with People Culture Talent. We're excited to help connect talented professionals with this exceptional team!