Snorkel AI Senior Software Engineer at Snorkel AI to build and operate large-scale AI systems supporting frontier AI research labs. The role involves designing scalable distributed systems and integrating advanced AI/ML technologies.
Responsibilities
Snorkel AI, Inc. seeks a Senior Software Engineer in San Francisco, CA to build systems to power large-scale AI workloads for top tier AI research labs. Work closely with other engineers, product managers, and field team members to ensure that Snorkel’s frontier AI datasets meet and surpass the capabilities of the most advanced foundation models. Launch agents into production to accomplish long running reasoning and verification tasks. The Evaluation Engineering team owns critical systems for building high-quality post-training and benchmark datasets, integrating with the latest foundation model technology to push the frontier of models used globally across coding, mathematics, law, medicine, and other advanced domains. Own the architecture, design, development, and operations of large-scale systems designed for AI/ML tasks including distributed compute systems, data management systems, data engineering workflow systems, and end user experiences. Recognize and act on opportunities to integrate the latest agentic and foundation model technologies to power eval workflows. Prototype, optimize, and maintain scalable back-end services that will power new foundation model development tools. Design extensible and testable interfaces between internal services including the underlying storage and data models. Be an engaged team player in a customer-focused cross-functional environment where you will feel excited to take on whatever is most impactful for the company and product.
Qualification
3 years designingAble to work 100% remotelyUnited States (Remote)Salary range(s) for this role$208
Required
Bachelor’s degree (or foreign equivalent) in Computer Science or a related field and the following experience:
4 years developing software using Java & Typescript and work with relational databases, with a focus on scalability, reliability and performance;
4 years building and optimize large-scale distributed systems or compute frameworks for data processing;
3 years designing, developing and delivering AI/ML systems and services in production environments for cloud-native applications, development of AI agents and LLM-powered systems: Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP);
3 years designing and implementing data storage, compute & retrieval systems to support AI/ML applications;
3 years improving large language model (LLM) applications through evaluation frameworks, prompt engineering and agent orchestration techniques;
3 years leading or owning the delivery of large, multi-person engineering projects from design through deployment.
Able to work 100% remotely.
United States (Remote)
Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.