Jobs at Thinking Machines Lab

Lead a team of engineers to design and scale reliable ML systems, ensure high execution standards, and collaborate with tech leads and product teams.

The HR Business Partner will coach managers, advise on organizational decisions, design compensation structures, and build evaluation processes to support employee growth and performance.

The designer will create end-to-end product experiences, collaborate on AI model training, and contribute to design systems and branding.

The Compensation Partner will design and implement compensation frameworks, advise on pay decisions, and develop equity compensation strategies to attract and retain talent.

Lead the corporate legal function: manage equity and financing transactions, corporate governance, cap table and board matters, and subsidiary maintenance. Build and scale commercial contracting (partnerships, vendor, licensing, data, research collaborations), templates, playbooks, and approval workflows. Advise execs, finance, product, engineering, and board on legal and risk issues for AI products.

The Executive Business Partner will manage calendars, coordinate travel, support recruiting, and track projects for technical leaders in a fast-paced startup environment.

The Technical Sourcer will identify and engage exceptional technical candidates, develop sourcing strategies, and build community engagement for recruitment efforts.

As a Research Product Manager, drive complex research products, translate technical ideas into plans, collaborate across disciplines, and maintain progress communication.

The role focuses on designing and implementing data curation techniques for AI pre-training datasets, ensuring quality, collaboration, and continuous improvement of data processing systems.

The Site Reliability Engineer will drive reliability for the Tinker platform, focusing on incident response, monitoring, and ensuring system resilience while collaborating across teams.

The Forward Deployed Engineer will support customers by diagnosing issues, improving products, building tools, and informing Tinker's roadmap.

The Research Engineer will design, optimize, and scale systems for large AI models, enhancing performance, reliability, and efficiency in model inference and deployment.

Design and optimize large-scale distributed training infrastructure, focusing on numerical methods to enhance efficiency and stability in AI model training.

The role involves designing and optimizing distributed training systems for large models to enhance research efficiency and productivity in AI.

Design, build, and operate GPU supercomputing environments, automate large GPU clusters, and collaborate with researchers to optimize performance and resources.

The role involves building and shipping products and services for Tinker, including backend APIs, user-facing products, and improving system reliability and developer experience.

The Software Engineer at Tinker will develop the platform systems for billing, permissions, and data management. Responsibilities include designing authorization layers and managing end-to-end billing infrastructure, collaborating with teams, and ensuring compliance with enterprise requirements.

The Software Engineer, Data Infrastructure will design scalable systems for data processing and orchestration, collaborating with teams to enhance data quality and accelerate research.

Develop and maintain full stack applications focusing on APIs, UX, system reliability, security, and collaboration across teams.

Design and build infrastructure for scalable reinforcement learning, optimize RL training pipelines, and collaborate with researchers on production-grade solutions.