Systems Software Engineer - Machine Learning Ops

* Design, build, and optimize high-performance C++ systems 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 correctness across existing C++ codebases * Collaborate with data, research, and engineering teams to support model training and evaluation at scale * Identify bottlenecks and edge cases in data and system behavior — then implement scalable, production-grade fixes * Participate in synchronous design reviews to iterate on architecture and implementation decisions

Who You Are

* 5+ years of professional experience writing production-grade C++ * Full-stack developer with a strong systems programming background * Experience working with the C++ frontends of ML frameworks or inference runtimes * Familiar with hardware acceleration APIs for optimizing model inference * Native or fluent English speaker with clear written and verbal communication skills * Able to commit 20–40 hours per week consistently

Nice to Have

* Prior experience with data annotation, data quality pipelines, or evaluation systems * Familiarity with AI/ML workflows, model training, or benchmarking pipelines * Experience with distributed systems or developer tooling * Background in systems performance profiling and optimization

Why Join Us

* Work on production systems that directly influence the capabilities of frontier AI models * Collaborate with engineers and researchers at leading AI labs * Fully remote and flexible — work when and where it suits you * Freelance autonomy with the structure and purpose of high-stakes engineering work * Potential for ongoing engagement and expanded scope as new projects launch