Python Infrastructure Engineer — Model Evaluation (AI Training) About The Role What if your Python expertise could directly shape how the world's most advanced AI models are built, tested, and improved? We're looking for a senior Python engineer to design and build the data pipelines, evaluation harnesses, and annotation tooling that sit at the heart of cutting-edge AI development. This is a fully remote, flexible contract role working alongside leading AI research labs on real production systems. If you're a strong Python engineer who wants to do meaningful, high-impact work at the frontier of AI — this is the role for you. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 20–40 hours/week

What You'll Do

Design, build, and optimize high-performance Python systems supporting AI data pipelines and model evaluation workflows Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control Build and maintain evaluation harnesses that integrate with ML inference frameworks Improve reliability, performance, and safety across existing Python codebases Instrument systems with observability and metrics collection to monitor reliability and model performance Identify bottlenecks and edge cases in data and system behavior, and implement scalable fixes Collaborate with data, research, and engineering teams to support model training and evaluation workflows Participate in synchronous design reviews to iterate on architecture and implementation decisions Who You Are Native or fluent English speaker with clear written and verbal communication skills Full-stack developer with a strong systems programming background 3–5+ years of professional experience writing production-grade Python Experienced building evaluation harnesses for ML models and integrating with inference frameworks Solid background in observability, metrics collection, and monitoring for production systems Self-motivated and reliable — able to commit 20–40 hours per week

Nice to Have

Prior experience with data annotation, data quality, or evaluation systems Familiarity with AI/ML workflows, model training, or benchmarking pipelines Experience with distributed systems or developer tooling Background in MLOps or AI infrastructure

Why Join Us

Work directly on cutting-edge AI projects alongside leading research labs Fully remote and flexible — structure your work week around your life Freelance autonomy with the depth and consistency of meaningful, long-term technical work Make a tangible impact on how next-generation AI models are evaluated and improved Potential for ongoing work and contract extension as new projects launch