Systems Programmer - AI Data Pipelines

Systems Programmer — AI Data Pipelines

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