Systems Programmer - AI Data Pipelines
About this role
About the Role What if your mastery of Rust could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for a senior Rust engineer to design and build the high-performance data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve their models. This is a fully remote contract role working on real production systems — not toy projects. You'll be embedded alongside world-class data, research, and engineering teams, solving hard systems problems that have a direct impact on the trajectory of AI development. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 20–40 hours/week What You'll Do - Design, build, and optimize high-performance systems in Rust supporting large-scale AI data pipelines and evaluation workflows - Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale - Improve reliability, performance, and safety across existing Rust codebases - Identify and eliminate bottlenecks and edge cases in data and system behavior, implementing scalable, production-ready fixes - Collaborate closely with data, research, and engineering teams to support model training and evaluation workflows - Participate in synchronous design reviews to iterate on system architecture and implementation decisions Who You Are - Native or fluent English speaker with clear written and verbal communication skills - 3–5+ years of professional experience writing production-grade Rust - Deep command of Rust lifetimes, ownership mechanics, and idiomatic error handling — you write Rust the way it was meant to be written - Proven experience building I/O-bound data pipelines with robust retry/backoff logic for production environments - Self-directed and reliable — you can commit to 20–40 hours per week and deliver without hand-holding - Sharp eye for edge cases and system behavior under load Nice to Have - Prior experience with data annotation, data quality, or evaluation systems - Familiarity with AI/ML workflows, model training, or benchmarking pipelines - Experience with distributed systems architecture or developer tooling - Background working alongside research or ML engineering teams Why Join Us - Work on real, high-stakes AI infrastructure used by leading research labs - Fully remote and async-friendly — work from anywhere, on a schedule that suits you - Meaningful, technically challenging problems — not maintenance work - Direct impact on how next-generation AI systems are built, evaluated, and improved - Potential for ongoing work and contract extension as new projects launch
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