Systems Programmer - AI Data Pipelines

Job summary

Seattle
Software Developer

Work model

Fully remote
Worldwide
2 days ago
Job description

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

What You'll Do

  • 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

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 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

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 or developer tooling
  • Background working alongside research or ML engineering teams

Why Join Us

  • 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