Principal Rust Engineer - ML Infrastructure

Principal Rust Engineer — ML Infrastructure (AI Training)

About the Role

What if your mastery of Rust could directly shape the infrastructure powering next-generation AI models? We're looking for a Principal Rust Engineer to design and build the high-performance systems that leading AI labs depend on — from data pipelines and annotation tooling to evaluation frameworks that run at production scale.

This is a fully remote contract role working alongside world-class research and engineering teams. If you live and breathe Rust and want your work to matter at the frontier of AI development, this is built for you.

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

What You'll Do

• Design, build, and optimize high-performance Rust systems supporting AI data pipelines and model evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
• Improve reliability, performance, and memory safety across existing Rust codebases
• Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation
• Identify bottlenecks and edge cases across data and system behavior — then implement scalable, production-grade fixes
• 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 applications
• Deep expertise in memory management and zero-copy deserialization with minimal runtime overhead
• Experienced integrating Rust with machine learning frameworks or columnar data standards to support training workflows
• Self-directed and dependable — able to commit 20–40 hours per week and deliver with minimal hand-holding

Nice to Have

• Prior experience with data annotation, data quality systems, or evaluation pipelines
• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
• Background in distributed systems or developer tooling

Why Join Us

• Work directly with leading AI labs on real production systems — not toy projects
• Fully remote and async-friendly — work on your own schedule from anywhere
• Freelance autonomy with the structure and focus of meaningful, high-stakes engineering work
• Build infrastructure that shapes how next-generation AI models are trained and evaluated
• Potential for ongoing work and contract extension as new projects launch