Senior C# Engineer - AI Infra & Tooling (Remote)

Alignerr Corp.; Seattle (WA); Remote; USD 83,000 - 124,000; Full time

Job summary

Alignerr is seeking a senior full-stack C# engineer to design and optimize internal tooling, data pipelines, and evaluation systems powering AI research. This remote hourly contract covers 20-40 hours per week, with production-grade responsibilities across data annotation, validation, and model evaluation.

You will work on high-performance C# systems, integrate Python ML models from .NET, and improve reliability across codebases while collaborating with data, research, and engineering teams.

Qualifications

• 3–5+ years of professional experience writing production-grade C#.
• Experience with cross-language integration (Python <-> .NET) preferred.
• Strong English written and verbal communication.
• Ability to commit 20–40 hours per week reliably.

Responsibilities

• 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 bottlenecks and edge cases in data and system behavior, then implement scalable fixes.
• Participate in synchronous design reviews to iterate on architecture and implementation decisions.

Skills

C#

Full-stack development

Python interop

Cross-language integration

Performance benchmarking

Reliability & consistency

Tools

NET

Job description

Alignerr is seeking a senior full-stack C# engineer to design and optimize internal tooling, data pipelines, and evaluation systems powering AI research. This remote hourly contract covers 20-40 hours per week, with production-grade responsibilities across data annotation, validation, and model evaluation.

You will work on high-performance C# systems, integrate Python ML models from .NET, and improve reliability across codebases while collaborating with data, research, and engineering teams.