People Culture Talent
Software Engineer – ML Infrastructure
- Location
- San Francisco, CA, US
- Arrangement
- On-site
- Employment type
- Full-time
- Posted
- 11 November 2026 (4 days ago)
Checked 3 days agoApplications go to the employer, never to RoleSprint
About this role
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!
THE ROLE
We’re seeking an experienced ML Infrastructure Software Engineer to build and improve infrastructure for machine learning workloads. You’ll partner with researchers and engineers to support experimentation, training, evaluation, and production deployment, with a focus on reliability and performance.
WHAT YOU’LL OWN
- 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.
WHAT YOU’LL BRING
- 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.
PREFERRED EXPERIENCE
- 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.
Work location
- San Francisco, CA, US
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About this listing
Published on Ashby under the board identifier People Culture Talent, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.
RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.
Published 11 November 2026, last checked 3 days ago. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.