About this role · Coding
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 Infrastructure Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and validate next-generation models. This is a fully remote contract role with flexible hours — you'll be working on real production systems at the cutting edge of AI development. - 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 for ML models, integrating with inference frameworks - Improve reliability, performance, and safety across existing Python codebases - Implement observability, metrics collection, and monitoring to track system reliability and model performance - Identify bottlenecks and edge cases in data and system behavior, and ship scalable fixes - Collaborate with data, research, and engineering teams to support model training and evaluation workflows - Participate in synchronous design reviews to iterate on system 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 - Strong background in observability, metrics collection, and system reliability monitoring - Able to commit 20–40 hours per week consistently - Self-directed and comfortable working asynchronously across distributed teams 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, infrastructure engineering, or platform engineering Why Join Us - Work on real production systems powering some of the most advanced AI research in the world - Fully remote and flexible — structure your work around your life - Freelance autonomy with the depth and meaning of high-impact engineering work - Contribute directly to AI infrastructure that shapes how next-generation models are built and evaluated - Potential for ongoing work and contract extension as new projects launch