Remote Senior C# Engineer — AI Pipelines & Evaluation

Alignerr; Mexico; On-site; PHP 5,156,000 - 9,453,000; Part time

Benefits offered by this job

Fully remote

Freelance autonomy

Contract extension potential

Job summary

Alignerr is seeking a senior full-stack C# engineer to build data pipelines, annotation systems, and evaluation tooling powering AI infrastructure. You will write production code at the heart of AI training and evaluation workflows—the kinds of systems that determine how models learn, improve, and get measured.

This is a remote hourly contract offering 20–40 hours per week. You will collaborate with data, research, and engineering teams across model training and evaluation, delivering scalable,

Qualifications

• 3–5+ years of production-grade C# experience.
• Clear and precise written and verbal communication in English.
• Ability to commit 20–40 hours per week consistently.

Responsibilities

• Design and build high-performance C# systems for 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 benchmarking and evaluation harnesses to measure system behavior.
• Implement interoperability solutions — calling Python ML models from .NET or wrapping native libraries.
• Identify bottlenecks and ship scalable, well-reasoned fixes.
• Collaborate with data, research, and engineering teams across model training and evaluation workflows.

Skills

C# development

Full-stack development

Python interop

Benchmarking

Performance tuning

Job description

Alignerr is seeking a senior full-stack C# engineer to build data pipelines, annotation systems, and evaluation tooling powering AI infrastructure. You will write production code at the heart of AI training and evaluation workflows—the kinds of systems that determine how models learn, improve, and get measured.

This is a remote hourly contract offering 20–40 hours per week. You will collaborate with data, research, and engineering teams across model training and evaluation, delivering scalable,