Senior Python Full-Stack Engineer — AI Data & Infrastructure

About The RoleWhat if your Python expertise could directly shape the data pipelines and evaluation systems powering the world's most advanced AI models? We're looking for Senior Python Full-Stack Engineers to design and build the critical infrastructure that leading AI labs depend on — from high-performance data annotation tooling to scalable evaluation workflows.This is a fully remote, flexible contract role with serious technical depth and real production impact. If you've spent years writing Python that actually ships and scales, this is where that experience pays off.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 20–40 hours/weekWhat You'll DoDesign, build, and optimize high-performance Python systems supporting AI data pipelines and evaluation workflowsDevelop full-stack tooling and backend services for large-scale data annotation, validation, and quality controlImprove reliability, performance, and safety across production Python codebasesCollaborate with data, research, and engineering teams to support model training and evaluation workflowsIdentify bottlenecks and edge cases in data and system behavior — then implement scalable, lasting fixesParticipate in synchronous design reviews to iterate on architecture and implementation decisionsWho You AreNative or fluent English speaker with clear written and verbal communication skillsExperienced full-stack developer with a strong systems programming background5+ years of professional experience writing production-grade PythonDeep understanding of performance optimization and concurrency — asyncio, multiprocessing, threadingComfortable with type safety tooling such as Pydantic and mypyProven track record building robust backend services (FastAPI, Django) or scalable data pipelinesAble to commit 20–40 hours per week with reliability and professionalismNice to HavePrior experience with data annotation, data quality systems, or evaluation pipelinesFamiliarity with AI/ML workflows, model training, or benchmarking infrastructureExperience with distributed systems or developer toolingBackground working directly with research or ML engineering teamsWhy Join UsWork on real production systems alongside leading AI research labsFully remote and flexible — structure your hours around your lifeFreelance autonomy with the substance and challenge of high-impact technical workMake a direct, measurable contribution to the infrastructure powering next-generation AIPotential for ongoing work and contract extension as new projects launch