Senior Machine Learning Expert (AI Training) About the Role What if your deep knowledge of machine learning could directly shape how the world's most advanced AI systems reason, plan, and make decisions?
Principal Rust Engineer - ML Infrastructure
Remote (Global)
$50 – $75/hr
July 14, 2026
Job description
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
Apply now
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