Principal Rust Engineer --- ML Infrastructure (AI Training) About The Role What if your deep mastery of Rust could directly shape the infrastructure that powers the world's most advanced AI models? We're looking for a Principal Rust Engineer to build, optimize, and harden the high-performance systems that leading AI labs depend on --- from data pipelines and annotation tooling to evaluation frameworks that influence how next-generation models are trained.
This is a fully remote, flexible contract role for an experienced engineer who writes production-grade Rust and thrives at the intersection of systems programming and AI infrastructure.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20--40 hours/week
What You'll Do
- Design and build high-performance, production-grade 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 used in real AI production environments
- Collaborate with data, research, and engineering teams to support model training and evaluation workflows
- Identify bottlenecks, edge cases, and systemic issues --- then implement scalable, elegant solutions
- Participate in synchronous design reviews to iterate on architecture and implementation decisions
Who You Are
- Native or fluent English speaker with clear written and verbal communication skills
- 5+ years of professional experience writing production Rust for data-intensive or systems-level applications
- Deep understanding of memory management, ownership semantics, and zero-copy deserialization with minimal runtime overhead
- Experienced integrating Rust with machine learning frameworks or columnar data standards to support model training workflows
- Able to commit 20--40 hours per week with consistency and reliability
- Self-directed and comfortable working asynchronously across distributed teams
Nice to Have
- Prior experience with data annotation pipelines, data quality systems, or evaluation infrastructure
- Familiarity with AI/ML workflows, model training, or benchmarking pipelines
- Background in distributed systems architecture or developer tooling
- Experience working directly with AI research teams or in a fast-moving lab environment
Why Join Us
- Work on real production systems powering cutting-edge AI research at leading labs
- Fully remote and flexible --- structure your hours around your life
- Freelance autonomy with the substance of high-impact, technically challenging work
- Collaborate with world-class engineers and researchers at the frontier of AI development
- Potential for ongoing work and contract extension as new projects launch
