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 design and build high-performance systems at the heart of real AI research and production workflows — working alongside leading AI labs on the tools and pipelines that make cutting-edge AI possible.

This is a fully remote, flexible contract role for an experienced Rust engineer who thrives on hard technical problems, cares deeply about performance and correctness, and wants their work to matter at scale.

• 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 production Rust codebases
• Collaborate with data, research, and engineering teams to accelerate model training and evaluation workflows
• Identify and resolve bottlenecks and edge cases in complex data and system behavior
• Participate in synchronous design reviews and contribute to high-impact architectural decisions
  
  

Who You Are

• Native or fluent English speaker with clear written and verbal communication skills
• 5 years of professional experience writing production-grade Rust for data-intensive applications
• Deep expertise in memory management, ownership semantics, 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 reliable availability
• You write code that other senior engineers learn from — and you're proud of it
  
  

Nice to Have

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

Why Join Us

• Work on real production systems for leading AI research labs — not toy problems
• Fully remote and flexible — work when and where you do your best thinking
• Freelance autonomy with the structure of meaningful, high-impact engineering work
• Contribute to infrastructure that directly shapes how next-generation AI models are built and evaluated
• Potential for ongoing work and contract extension as projects grow and evolve