Software Engineer (C#) - Internal Tooling
Indexed description
This is a fully remote contract role with flexible commitment. You'll work on real production systems alongside data, research, and engineering teams at the frontier of AI development.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
- Design, build, and optimize high-performance C# systems supporting AI data pipelines and evaluation workflows
- Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
- Improve reliability, performance, and safety across existing C# codebases
- Collaborate with data, research, and engineering teams to support model training and evaluation workflows
- Identify and resolve bottlenecks and edge cases in data and system behavior with scalable solutions
- Participate in synchronous design reviews to iterate on architecture and implementation decisions
- Build and maintain robust benchmarking and performance evaluation harnesses
- 3–5+ years of professional experience writing production-grade C#
- Strong full-stack developer background with solid systems programming fundamentals
- Expertise in interoperability scenarios — such as invoking Python ML models from .NET or wrapping native libraries
- Experienced designing robust harnesses for benchmarking and evaluating system performance
- Native or fluent English speaker with clear written and verbal communication skills
- Able to commit 20–40 hours per week with reliability and consistency
- Prior experience with data annotation, data quality, or evaluation systems
- Familiarity with AI/ML workflows, model training, or benchmarking pipelines
- Experience with distributed systems or developer tooling
- Background working with or alongside research teams in a fast-moving environment
- Work on cutting-edge AI projects alongside leading research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact technical work
- Build systems that directly influence how next-generation AI models are trained and evaluated
- Potential for ongoing work and contract extension as new projects launch
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