Job Opportunities API

ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.   ABOUT THE ROLE As a Senior Software Engineer on our Coding Pod, you'll lead the design and development of the data infrastructure that powers frontier AI coding models. This team sits at the intersection of applied machine learning, distributed systems, and developer tooling—building the large-scale benchmark datasets, evaluation frameworks, and execution environments that determine how state-of-the-art coding models are trained and measured. You'll own critical platform investments end-to-end, from architecting scalable data pipelines and evaluation systems to establishing technical standards for dataset quality, reliability, and developer workflows. Working closely with ML researchers, product managers, and engineers, you'll translate ambiguous research goals into production-ready systems that accelerate model development and improve evaluation quality. This is an opportunity to shape the infrastructure behind next-generation AI coding systems while solving challenging distributed systems, data engineering, and developer platform problems at scale. Location: San Francisco, CA     WHAT YOU'LL DO - Architect and build scalable data infrastructure that powers the generation, transformation, validation, and delivery of large-scale coding datasets. - Design end-to-end evaluation systems, including automated grading, benchmarking, human-in-the-loop review, and quality assurance workflows. - Lead the technical design of developer-facing tooling and integrations with engineering ecosystems (GitHub, CI/CD systems, coding agents, containerized execution environments). - Build reliable backend services and APIs that support dataset generation, evaluation pipelines, and experiment infrastructure. - Drive architectural decisions around distributed systems, workflow orchestration, execution environments, and data quality. - Partner closely with ML researchers to translate evolving evaluation methodologies into scalable engineering systems. - Improve platform reliability, observability, and performance through monitoring, debugging, and operational excellence. - Mentor engineers through technical design reviews, code reviews, and architectural guidance while helping raise the engineering bar across the team. - Identify opportunities to standardize reusable infrastructure, tooling, and evaluation frameworks that accelerate future model development.     WHAT WE'RE LOOKING FOR - 6+ years of professional software engineering experience building backend syst