C# Infrastructure Engineer - Data Pipelines

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Description

Build production AI infrastructure

Design and improve C# systems that support AI data pipelines, training and evaluation. Work on production code, with emphasis on dependable services, efficient processing and practical research tooling.

Build backend services and tools for data annotation, validation and quality control at scale.
Improve reliability, performance and correctness in existing codebases.
Find system bottlenecks, data edge cases and failure modes, then implement fixes that support growing workloads.
Coordinate with data, research and engineering groups around model training and evaluation needs.
Participate in live technical design reviews covering architecture and implementation.

Required engineering experience

The role calls for 5+ years of professional production experience in C#. A strong full-stack development background and systems programming foundation are required.

You need substantial experience with asynchronous streams and reactive programming in streaming pipelines. Optimizing I/O-bound work and designing resilient retry policies for distributed ingestion are required skills.

Native or fluent English is required, with clear written and spoken communication. Consistent availability for 20–40 hours per week is required, along with dependable delivery in a remote engineering environment.

Helpful additional background

Experience with annotation systems, data quality processes or model evaluation is useful. Familiarity with AI/ML workflows, training or benchmarking infrastructure, distributed systems and developer tooling also strengthens a candidacy.

Contract and collaboration

This is a fully remote hourly contract with flexible working arrangements. The commitment is 20–40 hours each week, with technical reviews and cross-functional collaboration forming part of the work.

The arrangement combines freelance independence with production engineering assignments. Continued projects and contract extensions may become available as new research work launches.