Senior C# Full-Stack Engineer — AI Data & Infrastructure
Software & Coding
$50-$75/hr
About this role · Coding
About the Role What if your C expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a Senior C Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — working on real production systems with genuine, measurable impact. This is a fully remote contract role with flexible hours. If you're a sharp systems thinker who loves solving hard infrastructure problems, this is the kind of work that will actually push you. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 20–40 hours/week What You'll Do - Design, build, and optimize high-performance C 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 - Improve reliability, performance, and safety across existing C codebases — hunt down bottlenecks and ship scalable fixes - Collaborate directly with data, research, and engineering teams to support model training and evaluation workflows - Identify edge cases and systemic issues in data and system behavior and implement robust solutions - Participate in synchronous design reviews to iterate on architecture and implementation decisions Who You Are - Full-stack developer with a strong systems programming background and 3–5+ years of professional C experience - Confident writing production-quality code with a focus on modern C standards and best practices - Deep understanding of performance optimization, concurrency (threading, atomics), and memory safety - Clear, precise written and verbal communicator — you can articulate technical decisions without hand-waving - Self-directed and reliable when working remotely with minimal supervision - Native or fluent English speaker - Able to commit 20–40 hours per week on a consistent basis Nice to Have - Prior experience with data annotation, data quality pipelines, or AI evaluation systems - Familiarity with AI/ML workflows, model training, or benchmarking infrastructure - Experience with distributed systems or developer tooling - Background working in fast-moving research or applied ML environments Why Join Us - Work directly with leading AI labs on cutting-edge production systems — not toy projects - Fully remote and flexible — structure your work around your life - Freelance autonomy with the focus and momentum of high-impact engineering work - Collaborate with world-class data, research, and engineering teams pushing the frontier of AI - Potential for ongoing work and contract extension as projects scale