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 full-stack C# engineer to build the data pipelines, annotation systems, and evaluation tooling that leading AI labs depend on every day.
This isn't toy work or proof-of-concept territory. You'll be writing production code that sits at the heart of real AI training and evaluation workflows — the kind of systems that determine how models learn, improve, and get measured.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
What You'll Do
- Design and build high-performance C# systems that support 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 correctness across existing C# codebases
- Build robust benchmarking and evaluation harnesses to measure system behavior
- Implement interoperability solutions — such as invoking Python ML models from .NET or wrapping native libraries
- Identify bottlenecks and edge cases, then ship scalable, well-reasoned fixes
- Collaborate with data, research, and engineering teams across model training and evaluation workflows
- Participate in synchronous design reviews to iterate on architecture and implementation decisions
Who You Are
- 3–5+ years of professional experience writing production-grade C#
- Strong full-stack developer with a solid systems programming foundation
- Experienced in interoperability scenarios — calling Python ML models from .NET, wrapping native libraries, bridging ecosystems
- Proven track record designing benchmarking harnesses and performance evaluation systems
- Clear, precise written and verbal communicator — you can explain technical decisions to mixed audiences
- Native or fluent English speaker
- Able to commit 20–40 hours per week consistently
Nice to Have
- Prior experience with data annotation platforms, data quality pipelines, or 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 AI-adjacent engineering environments
Why Join Us
- Work on real production systems alongside top AI research labs — not toy demos
- Fully remote and flexible — structure your hours around your best work
- Freelance autonomy with the substance of meaningful, high-stakes engineering
- Make a tangible impact on the infrastructure that shapes how next-generation AI models are built and evaluated
- Potential for ongoing work and contract extension as projects grow