Backend Developer - Data Annotation Systems
About this role
About the Role What if your Python expertise could directly shape the infrastructure that trains the world's most advanced AI models? We're looking for a Senior Python Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on every day. This is a fully remote, flexible contract role for a seasoned engineer who wants to work on real production systems — not toy projects — alongside top-tier research and engineering teams. - 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 large-scale AI data pipelines and model evaluation workflows - Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale - Build and maintain asynchronous task queues to handle long-running background jobs reliably - Optimize database queries for high-read/write workloads and serve data via real-time protocols including WebSockets - Improve reliability, performance, and safety across existing production Python codebases - Collaborate with data scientists, researchers, and engineers to support model training and evaluation workflows - Identify bottlenecks and edge cases across data systems and implement scalable, production-grade fixes - Participate in synchronous design and code reviews to drive sound architectural decisions Who You Are - 3–5+ years of professional experience writing production-grade Python - Strong full-stack developer with a solid systems programming background - Experienced building asynchronous task queues and background job systems - Proficient in optimizing database queries for high-throughput applications - Comfortable serving and consuming real-time data via WebSockets or similar protocols - Clear, precise written and verbal communicator — you can articulate technical decisions well - Native or fluent English speaker - Able to commit 20–40 hours per week consistently Nice to Have - Prior experience with data annotation platforms, data quality systems, or model evaluation infrastructure - Familiarity with AI/ML workflows, model training pipelines, or benchmarking systems - Experience designing or maintaining distributed systems - Background in developer tooling or internal platform engineering Why Join Us - Work on cutting-edge AI infrastructure alongside leading research labs — this is real, high-stakes work - Fully remote and async-friendly — work from wherever you do your best thinking - Freelance autonomy with the structure and consistency of meaningful, ongoing project work - Make a direct, tangible impact on how next-generation AI models are built, trained, and evaluated - Potential for ongoing work and contract extension as new projects and partnerships launch
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