About the job
At Thinking Machines Lab, our vision is to enhance human potential by advancing collaborative general intelligence. We are dedicated to creating a future where individuals have the resources and knowledge to harness AI for their specific objectives and aspirations.
Our team comprises scientists, engineers, and innovators who have developed some of the most popular AI products, including ChatGPT and Character.ai, as well as influential open-weight models like Mistral, along with highly regarded open-source projects such as PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
About the Role
We are seeking a talented engineer to enhance our data infrastructure. You will become part of a dynamic, high-impact team tasked with designing and scaling the foundational infrastructure for distributed training pipelines, multimodal data catalogs, and sophisticated processing systems that manage petabytes of data.
Our infrastructure is pivotal; it serves as the foundation for every groundbreaking achievement. You will collaborate directly with researchers to expedite experiments, develop novel datasets, optimize infrastructure efficiency, and derive essential insights from our data repositories.
If you are passionate about distributed systems, large-scale data mining, and open-source tools such as Spark, Kafka, Beam, Ray, and Delta Lake, and enjoy building innovative solutions from scratch, we encourage you to apply.
Note: This is an evergreen role that we keep open continuously for expressions of interest. We receive a high volume of applications, and while there may not always be an immediate position that aligns perfectly with your skills and experience, we encourage you to apply. We regularly review applications and reach out as new opportunities arise. You are welcome to reapply after gaining more experience, but please refrain from applying more than once every six months. We may also post for specific roles for particular projects or team needs, and in those cases, you are welcome to apply directly in addition to this evergreen role.

