Systems Programmer - AI Data Pipelines

About The Role

What if your Rust expertise could directly shape the infrastructure powering the next generation of AI models? 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 collaborate directly with data, research, and engineering teams on infrastructure that matters at scale.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

• Design, build, and optimize high-performance systems in Rust supporting AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
• Improve reliability, performance, and safety across existing Rust codebases
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Identify bottlenecks and edge cases in data and system behavior, and implement scalable fixes
• Participate in synchronous design reviews to iterate on system architecture and implementation decisions

• 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 code that's safe and maintainable by design
• Experienced building I/O-bound data pipelines with robust retry/backoff logic for production environments
• Self-directed and reliable — able to commit 20–40 hours per week and deliver without hand-holding
• You think in systems: performance, fault tolerance, and correctness aren't afterthoughts

• Prior experience with data annotation, data quality, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience with distributed systems or developer tooling
• Background working alongside research or ML engineering teams

• Work on cutting-edge AI infrastructure alongside top research labs and engineering teams
• Fully remote — work from wherever you do your best work
• Meaningful, high-impact work on systems that directly influence model quality at scale
• Freelance autonomy with consistent, structured engagement
• Potential for ongoing collaboration and contract extension as new projects launch