Systems Software Engineer - Machine Learning Ops

The work

Build and improve C++ systems for AI data pipelines, annotation, and model evaluation. This remote hourly contract involves 20 to 40 hours per week and includes live design discussions with research and engineering teams.

Responsibilities

• Design and optimize performant C++ components for data processing and evaluation workflows.
• Develop full stack tools and backend services supporting large scale annotation, data validation, and quality checks.
• Improve the reliability, performance, and correctness of production C++ software.
• Find bottlenecks, failure modes, and unusual data or system behavior, then implement scalable fixes.
• Coordinate with data, research, and engineering colleagues on training and evaluation requirements.
• Take part in live design reviews to refine architecture and implementation.

Background and skills

You need at least 5 years of professional experience producing C++ software, with strong systems programming and full stack development skills. Experience with C++ interfaces for machine learning frameworks or inference runtimes is required. Familiarity with hardware acceleration APIs used to improve model inference is also needed.

Native or fluent English and clear written and spoken communication are required. You must be dependable about a 20 to 40 hour weekly commitment and comfortable delivering work independently.

Additional strengths

Helpful experience includes annotation and data quality pipelines, evaluation systems, AI workflows, training and benchmarking, distributed systems, or developer tools. Systems profiling and performance optimization are also welcome.

Working arrangements

This is a remote hourly contract with a commitment of 20 to 40 hours each week. Work is organized around independent assignments and a flexible schedule. The work accommodates asynchronous delivery alongside synchronous design reviews.

Further projects may lead to continued engagements or contract extensions.