Senior Systems Engineer — AI Data & Infrastructure

Build production AI infrastructure

Design and improve Go, Rust, Python or 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.
• Contribute to architecture and implementation reviews.

Required engineering experience

The role calls for 5+ years of professional production experience in Go, Rust, Python or C++. Practical systems knowledge and reliable independent delivery are important.

Strong systems or backend engineering experience is required, with a record of building reliable services, internal tools or data pipelines. Good judgment about performance, reliability and correctness at scale is important.

Clear written and spoken communication is required for technical discussions and research collaboration. 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.