Software Engineer (C#) - Internal Tooling

Alignerr Corp.; United States; Remote; GBP 55,000 - 110,000; Part time

Job summary

Alignerr is seeking a Software Engineer (C#) to join internal tooling for AI infrastructure. You will design and optimize high-performance C# systems that power data pipelines, annotation, and evaluation tooling used by leading AI labs.

This remote hourly contract role offers 20–40 hours per week, with opportunities to extend as new projects launch. You will bridge .NET and Python ML workflows and work with cross-functional teams to ship production-grade solutions.

Qualifications

• 3–5+ years of production-grade C# experience.
• Strong full-stack and systems programming background.
• Experience calling Python ML models from .NET.
• Experience building benchmarking/evaluation harnesses.
• Excellent written and verbal communication; fluent English.

Responsibilities

• Design, build, and optimize high-performance C# systems for large-scale AI pipelines.
• Develop full-stack tooling and backend services for data annotation and validation.
• Improve reliability and performance of production C# codebases.
• Bridge .NET and Python ML ecosystems for model invocation and interoperability.
• Build benchmarking harnesses to evaluate system performance.
• Collaborate with data, research, and engineering teams to support training workflows.
• Participate in design reviews to iterate on architecture and implementation decisions.

Skills

C# production-grade

Full-stack developer

Python interop

Benchmarking harnesses

Clear communication

English fluency

Remote collaboration

Tools

.NET

Python

C#

Job description

Software Engineer (C#) — Internal Tooling (AI Infrastructure)

About The Role

What if your C# expertise could directly shape the infrastructure powering the next generation of AI? We're looking for experienced full-stack C# engineers to build and optimize the data pipelines, annotation systems, and evaluation tooling that leading AI labs depend on every day.

This isn't maintenance work or low-stakes ticket-churning. You'll be working on real production systems at the frontier of AI development — the kind of infrastructure that determines how AI models are trained, measured, and improved.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

What You'll Do

• Design, build, and optimize high-performance C# systems supporting 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 the reliability, performance, and safety of existing C# codebases used in production AI environments
• Bridge the gap between .NET and Python ML ecosystems — invoking models, wrapping native libraries, and enabling smooth interoperability
• Build robust benchmarking harnesses to evaluate system performance and surface edge cases
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Participate in synchronous design reviews to iterate quickly on architecture and implementation decisions

Who You Are

• 3–5+ years of professional experience writing production-grade C#
• Experienced full-stack developer with a strong systems programming background
• Skilled at interoperability scenarios — calling Python ML models from .NET, wrapping native libraries, crossing runtime boundaries cleanly
• Experienced designing benchmarking and evaluation harnesses for real systems
• Clear, precise written and verbal communicator — you can explain a design decision as well as implement one
• Native or fluent English speaker
• Able to commit 20–40 hours per week reliably

Nice to Have

• Prior experience with data annotation platforms, data quality systems, or evaluation pipelines
• Familiarity with AI/ML workflows, model training infrastructure, or benchmarking tooling
• Experience with distributed systems or internal developer tooling
• Background in performance engineering or systems-level optimization

Why Join Us

• Work on cutting-edge AI infrastructure alongside leading research labs and engineering teams
• Fully remote and flexible — structure your hours around your life
• Freelance autonomy with the depth and substance of meaningful, long-term engineering work
• Make a direct, tangible impact on how AI systems are built, evaluated, and improved at scale
• Potential for ongoing work and expanded scope as new projects launch