Principal Rust Engineer - ML Infrastructure

Principal Rust Engineer — ML Infrastructure (AI Training) About The Role

What if your deep expertise in Rust could directly shape the infrastructure powering some of the world's most advanced AI systems? We're looking for a Principal Rust Engineer to design and build the high-performance data pipelines, annotation tooling, and evaluation infrastructure that leading AI labs depend on to train and refine next-generation models.

This is a fully remote, flexible contract role for a seasoned Rust engineer who thrives on hard systems problems and wants their work to matter at scale.

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

• Design, build, and optimize high-performance Rust systems that power AI data pipelines and model evaluation workflows
• Develop full-stack backend tooling and services for large-scale data annotation, validation, and quality control
• Improve reliability, performance, and safety across production Rust codebases
• Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation
• Identify and resolve bottlenecks and edge cases in data flow and system behavior
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

• 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 understanding of memory management and zero-copy deserialization with minimal runtime overhead
• Proven experience 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 operating in fast-moving, research-adjacent environments

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

• Work on real production systems used by leading AI research labs
• Fully remote and async-friendly — work when and where it suits you
• Freelance autonomy paired with high-impact, technically demanding work
• Contribute directly to the infrastructure that makes next-generation AI possible
• Potential for ongoing work and contract extension as new projects launch