Data Platform Engineer (Python)

About The RoleWhat if your Python expertise could directly shape the infrastructure powering next-generation AI? 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 to train and improve their models.This is a fully remote contract role working on real production systems — not toy projects. You'll be embedded alongside data, research, and engineering teams doing meaningful, high-visibility work at the frontier of AI development.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 20–40 hours/weekWhat You'll DoDesign, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and evaluation workflowsDevelop full-stack tooling and backend services for data annotation, validation, and quality controlIdentify and fix bottlenecks, edge cases, and reliability issues across production Python codebasesCollaborate directly with data, research, and engineering teams to support model training and benchmarkingParticipate in synchronous design reviews to iterate on architecture and implementation decisionsImprove performance, safety, and scalability across existing infrastructureWho You AreNative or fluent English speaker with clear written and verbal communication skills5+ years of professional experience writing production-grade Python for data engineeringStrong full-stack developer background with solid systems programming fundamentalsProficient with workflow orchestration tools for managing complex dependency graphsExperienced with dataframe processing libraries and cloud data warehouse SDKsAble to commit reliably to 20–40 hours per weekNice to HavePrior experience with data annotation, data quality pipelines, or evaluation systemsFamiliarity with AI/ML workflows, model training, or benchmarking infrastructureExperience with distributed systems or developer toolingWhy Join UsWork on cutting-edge AI projects alongside leading research labs at the frontier of the fieldFully remote and flexible — work from wherever you do your best thinkingFreelance autonomy with the structure and consistency of meaningful, ongoing technical workMake a direct, tangible impact on the systems that shape how AI models learn and improvePotential for extended engagement and expanded scope as projects evolve