Data Infrastructure Engineer (Rust) - High Performance Computing

About The Role

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

This is a fully remote, flexible contract role for elite engineers who care about correctness, performance, and building systems that actually scale. If you've spent years thinking about memory layouts, concurrency patterns, and squeezing every cycle out of production systems — this is the role for you.

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

• Design, build, and optimize high-performance Rust systems supporting large-scale AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
• Hunt down and eliminate bottlenecks — profiling, identifying edge cases, and implementing durable, scalable fixes
• Improve reliability, safety, and performance across production Rust codebases
• Collaborate with data, research, and engineering teams to support model training and evaluation pipelines
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

• 5+ years of professional, production Rust experience — this is a must
• Deep expertise in data parallelism and concurrency patterns to maximize CPU saturation
• Strong command of memory layout, SIMD optimizations, and heap allocation strategies — you know how to find and fix performance bottlenecks
• Native or fluent English speaker with clear written and verbal communication skills
• Able to commit 20–40 hours per week with reliable availability
• Self-directed and confident making high-impact engineering decisions independently

• Prior experience with data annotation pipelines, data quality systems, or model evaluation infrastructure
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience building distributed systems or developer tooling
• Background working with or alongside research engineering teams

• Work on production systems that directly power cutting-edge AI research and development
• Fully remote and flexible — structure your week around your best working hours
• Freelance autonomy with the depth and impact of meaningful, high-complexity engineering work
• Collaborate with world-class engineers and researchers at leading AI labs
• Potential for ongoing work and contract extension across new projects as they launch