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RL Systems - Infra

Thinking MachinesSan FranciscoResearch Infrastructure (ML Infrastructure and Training Stack)
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Salary
$425K - $475K USD
Job type
Full-time
Experience
Senior
Posted
7 Oct 2026
Status
Open · checked 7d ago

About this role

San Francisco is the location for this infrastructure research engineer position at Thinking Machines, focusing on scalable reinforcement learning systems. This opportunity suits an experienced engineer who combines distributed systems expertise with deep learning knowledge.

Role Overview

Thinking Machines seeks an infrastructure research engineer to design and construct core systems supporting efficient, large-scale training of advanced models through reinforcement learning. The position bridges research and distributed systems engineering, requiring a professional who understands both reinforcement learning algorithms and large-scale training operations. Responsibilities involve optimizing rollout and reward pipelines while improving system reliability and orchestration.

Key Responsibilities

Design, build, and optimize infrastructure powering large-scale reinforcement learning and post-training workloads.
Improve reliability, scalability, and training throughput for distributed reinforcement learning workloads.
Develop shared monitoring and observability tools for high uptime, debuggability, and reproducibility.
Collaborate with researchers to translate algorithmic concepts into production-grade training pipelines.
Build evaluation and benchmarking infrastructure to measure progress on helpfulness, safety, and factuality.
Share technical insights through internal documentation, open-source libraries, or technical reports.

Requirements

Bachelor's degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or a related field.
Strong software engineering capabilities to write performant, maintainable code and debug complex codebases.
Understanding of deep learning frameworks and underlying system architectures.
Ability to thrive in a collaborative environment with cross-functional partners and subject matter experts.
Bias for action and initiative to work across various technical stacks and teams to ship solutions.

Nice to Have

Experience training or supporting large-scale language models featuring tens of billions of parameters or more.
Practical work with reinforcement learning workloads including PPO, DPO, RLHF, or reward modeling.
Background in high-performance or reliability engineering, distributed training frameworks, and cluster orchestration.
Familiarity with monitoring and observability platforms.
Contributions to large-scale machine learning research, infrastructure, or open-source frameworks.

Skills and Tools

PyTorch
JAX
Kubernetes
Slurm
Prometheus
Grafana
OpenTelemetry

Salary and Benefits

Annual salary range between $425,000 and $475,000 USD based on background, skills, and experience.
Health, dental, and vision benefits.
Unlimited paid time off.
Paid parental leave.
Relocation support as needed.

About the Company

Thinking Machines builds artificial intelligence designed to extend human will and judgment. The organization trains frontier models using Inkling, develops Tinker for personalized model creation, and designs interfaces to broaden human-AI communication.

How to Apply

Apply directly on the official company careers page.

Skills and tech stack

PyTorchJAXKubernetesSlurmPrometheusGrafanaOpenTelemetryReinforcement LearningDeep LearningMachine Learning

Questions candidates ask

Where is the job located?

The position is based in San Francisco, California.

What is the salary range for this role?

The expected annual salary ranges from $425,000 to $475,000 USD, depending on background, skills, and experience.

Does Thinking Machines offer visa sponsorship?

Yes, the company sponsors visas and works through the visa process with qualified candidates.

What educational background is required?

A bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or a similar field is required.

Is this an active immediate opening?

This is an evergreen role kept open on an ongoing basis to express interest, meaning immediate roles may not always be available.

Ready to apply?

The application is on the official Thinking Machines careers page.

Apply on company site