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