Staff Software Engineer, AI
Goodleap- Full Time
- Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates should hold an advanced degree in Computer Science, Engineering, or a related field and have demonstrable experience in distributed systems design and implementation. A proven track record of delivering early-stage projects under tight deadlines is essential, along with expertise in using cloud-based services such as elastic compute and managed databases. Experience in Generative AI, familiarity with AI infrastructure, and proficiency in software engineering skills such as container runtimes and REST APIs are also required. Preferred qualifications include proficiency in Golang or Python, contributions to open-source AI projects, and performance optimizations on GPU systems.
The Staff Software Engineer will lead the design and implementation of core AI services, including resilient fault-tolerant queues, model catalogs, and high-performance APIs. They will build and scale infrastructure to handle millions of API requests per second and optimize AI inference performance on GPU-based systems. The role involves collaborating closely with product management and other engineering teams, influencing architectural decisions, and contributing to open-source AI frameworks.
Utilizes wasted energy for computing power
Crusoe Energy Systems Inc. provides digital infrastructure that focuses on using wasted, stranded, or clean energy sources to power high-performance computing and artificial intelligence. The company helps clients in the technology and energy sectors by offering scalable computing solutions that aim to reduce greenhouse gas emissions and support the transition to cleaner energy. Crusoe's approach involves converting excess natural gas and renewable energy into computing power, which allows them to maximize resource efficiency while minimizing environmental impact. Unlike many competitors, Crusoe specifically targets the intersection of energy and technology, generating revenue by supplying computing resources to enterprises that need significant computational power for applications like AI and machine learning, along with providing technical support.