Backend Developer - Data Annotation Systems
About this role
About the Role What if your Python expertise could directly shape the infrastructure behind the world's most advanced AI systems? We're looking for a Senior Python Full-Stack Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve their models. This is a fully remote, flexible contract role with meaningful technical depth and real production impact. If you thrive on building systems that scale — and want to work on some of the most consequential infrastructure in AI right now — 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 that power AI data pipelines and evaluation workflows - Develop full-stack backend tooling and services for large-scale data annotation, validation, and quality control - Build and maintain asynchronous task queues to handle long-running background jobs reliably at scale - Optimize database queries for high-read/write workloads and serve data via real-time protocols including WebSockets - Identify bottlenecks, edge cases, and failure modes in data and system behavior — then implement robust, scalable fixes - Improve reliability, performance, and safety across existing Python codebases - Collaborate directly with data, research, and engineering teams supporting 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 - Experienced full-stack developer with a strong systems programming background - 3–5+ years of professional experience writing production-grade Python - Proven track record building asynchronous task queues for background processing at scale - Comfortable optimizing complex database queries and serving data in real time - Self-directed and reliable — you can commit 20–40 hours per week and deliver consistently Nice to Have - Prior experience with data annotation, data quality, or evaluation systems - Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure - Experience building or maintaining distributed systems or developer tooling Why Join Us - Work directly on production systems used by leading AI research labs - Fully remote and async-friendly — work from wherever you do your best work - Freelance autonomy paired with high-impact, technically meaningful projects - Collaborate with world-class researchers and engineers at the frontier of AI development - Potential for ongoing work and contract extension as new projects launch
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