Principal Rust Engineer - ML Infrastructure
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