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Software Engineer (C#) - Internal Tooling

Alignerr
Department:Design
Type:REMOTE
Region:Seattle, WA
Location:Seattle, WA
Experience:Mid-Senior level
Estimated Salary:$80,000 - $140,000
Skills:
C#FULL-STACK DEVELOPMENTSYSTEMS PROGRAMMINGAI/ML WORKFLOWSDATA PIPELINESBACKEND SERVICESDISTRIBUTED SYSTEMSPERFORMANCE BENCHMARKINGPYTHON INTEROPERABILITY
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Job Description

Posted on: February 27, 2026

About The JobAlignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. We work on real production systems and high-impact research workflows across data, tooling, and infrastructure. Position Senior C# Full-Stack Engineer — AI Data & InfrastructureType: Contract, Remote Commitment: 20–40 hours/week Compensation: Competitive, hourly (based on experience) Role Responsibilities

  • Design, build, and optimize high-performance systems in C# 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, and implement scalable fixes
  • Participate in synchronous reviews to iterate on system design and implementation decisions

QualificationsMust-Have

  • Native or fluent English speaker
  • Full-stack developer experience with a strong systems programming background
  • 3-5+ years of professional experience writing production C#.
  • Expertise in interoperability scenarios, such as invoking Python ML models from .NET or wrapping native libraries.
  • Experience designing robust harnesses for benchmarking and evaluating system performance.
  • Clear written and verbal communication skills.
  • Ability to commit 20–40 hours per week.

Preferred

  • 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

Application Process

  • Submit your resume
  • Complete a short technical screening
  • Project matching and onboarding
Originally posted on LinkedIn

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