Principal Python Engineer - ML Infrastructure

* Design, build, and optimize high-performance Python 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 reliability, performance, and safety across existing production Python codebases * Identify and resolve bottlenecks and edge cases in data and system behavior with scalable, well-engineered fixes * Collaborate with data, research, and engineering teams to support model training and evaluation workflows * Participate in synchronous design reviews to drive technical strategy and architectural decisions

Who You Are

* Native or fluent English speaker with clear written and verbal communication skills * 5+ years of professional experience writing production Python — specifically for large-scale infrastructure or platform engineering * Deep expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns * Strong command of Python internals — GIL limitations, memory profiling, and performance optimization for compute-heavy workloads * Full-stack development background with a strong systems programming foundation * Experienced driving technical strategy and contributing to architectural decisions at a senior or principal level * Able to commit 20–40 hours per week consistently

Nice to Have

* Prior experience with data annotation, data quality, or evaluation systems * Familiarity with AI/ML workflows, model training, or benchmarking pipelines * Background in distributed systems or developer tooling * Experience working directly with or adjacent to AI research teams

Why Join Us

* Work on real production systems alongside the world's leading AI labs — this is infrastructure that actually ships * Fully remote and flexible — work on your own schedule from anywhere * Freelance autonomy with the depth and complexity of principal-level engineering work * Make a direct, tangible impact on how next-generation AI models are built, evaluated, and improved * Potential for ongoing work and contract extension as new projects launch