Thinking Machines Lab
Site Reliability Engineer, Post Training
San Francisco · Mid
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About the role
- We're hiring a Site Reliability Engineer (SRE) to keep our post-training and reinforcement learning (RL) systems fast, reliable, and easy for researchers to iterate on.
- This role has real ownership: you'll be the person a research team calls when a run stalls at 2am, and the person who makes sure it doesn't happen again.
Responsibilities
- Own the reliability, performance, and uptime of large-scale post-training and RL training jobs, from launch through completion
- Partner directly with research teams during active model runs, embedding with them to unblock training and speed up iteration
- Debug failures across the full stack - accelerators, networking, storage, schedulers, and training frameworks - and drive issues to root cause
- Build monitoring, alerting, and automated recovery so runs self-heal or fail fast instead of silently stalling
- Build internal tools that reduce toil and improve cluster utilization across post-training and RL workloads
- Strong software engineering skills in Python and/or Go/C++, with the judgment to know when to script a fix versus build a system
Requirements
- 4+ years of experience as a production engineer, site reliability engineer, or infrastructure engineer operating large-scale distributed systems in production
- Track record debugging complex failures across distributed systems - networking, hardware, kernel, or scheduler issues
Nice to have
- Experience operating GPU or TPU training clusters at scale
- Familiarity with post-training and RL techniques (e.g., RLHF, PPO, DPO) and the infrastructure challenges specific to them, such as reward model serving, rollout generation, and mixed training/inference workloads
- Experience with distributed training frameworks (e.g., PyTorch, Ray) and job schedulers (e.g., Slurm, Kubernetes)
- Experience with high-performance networking (e.g., InfiniBand, RDMA, NCCL) and its role in distributed training performance
- A track record of thriving in fast-changing, research-driven environments where priorities shift with the science
- Visa sponsorship: We sponsor visas.
- While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
Compensation
- Depending on background, skills and experience, the expected annual salary range for this position is $300,000- $350,000 USD.
Benefits
- Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Company info
- The mission of Thinking Machines is to build AI that extends human will and judgment.
- We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication.
Visa & Work Authorization
- We sponsor visas.
- While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.