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 the next generation of AI models? We're looking for a Principal Rust Engineer to build and optimize the high-performance systems that leading AI labs depend on — from data pipelines and annotation tooling to evaluation infrastructure that drives model quality at scale.

This is a fully remote, flexible contract role for engineers who know Rust deeply and want to work on problems that actually matter. You'll collaborate directly with research and engineering teams at the frontier of AI development.

• 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 safety across production Rust codebases
• Identify bottlenecks and edge cases in data and system behavior, then implement scalable, lasting fixes
• Collaborate with data, research, and engineering teams to accelerate model training and evaluation workflows
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

Who You Are

• 5+ years of professional experience writing production-grade Rust for data-intensive applications
• Deep understanding of memory management, ownership semantics, and zero-copy deserialization with minimal runtime overhead
• Experience integrating Rust with machine learning frameworks or columnar data standards (e.g., Arrow, Parquet) to support model training workflows
• Strong written and verbal communication skills in English — you can articulate technical decisions clearly
• Able to commit 20–40 hours per week with a high degree of independence and reliability

Nice to Have

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

Why Join Us

• Work on real production systems used by leading AI research labs — not toy projects
• Fully remote and async-friendly — work from wherever you do your best thinking
• Freelance autonomy paired with meaningful, high-impact technical work
• Collaborate with world-class engineers and researchers at the cutting edge of AI
• Potential for ongoing work and contract extension as new projects launch