Principal Python Engineer - ML Infrastructure

Principal Python Engineer — ML Infrastructure (AI Training)About The RoleWhat if your Python expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a Principal Python Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve their most advanced models.This is a fully remote, flexible contract role for senior engineers who thrive on high-complexity, high-stakes infrastructure challenges. If you've spent years optimizing production Python at scale — and you want your work to matter — this is the opportunity.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 control at scaleImprove reliability, performance, and safety across existing production Python codebasesIdentify and resolve bottlenecks and edge cases in data and system behavior with scalable, well-engineered fixesCollaborate with data, research, and engineering teams to support model training and evaluation workflowsParticipate in synchronous design reviews to drive technical strategy and architectural decisionsWho You AreNative or fluent English speaker with clear written and verbal communication skills5+ years of professional experience writing production Python — specifically for large-scale infrastructure or platform engineeringDeep expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patternsStrong command of Python internals — GIL limitations, memory profiling, and performance optimization for compute-heavy workloadsFull-stack development background with a strong systems programming foundationExperienced driving technical strategy and contributing to architectural decisions at a senior or principal levelAble to commit 20–40 hours per week consistentlyNice to HavePrior experience with data annotation, data quality, or evaluation systemsFamiliarity with AI/ML workflows, model training, or benchmarking pipelinesBackground in distributed systems or developer toolingExperience working directly with or adjacent to AI research teamsWhy Join UsWork on real production systems alongside the world's leading AI labs — this is infrastructure that actually shipsFully remote and flexible — work on your own schedule from anywhereFreelance autonomy with the depth and complexity of principal-level engineering workMake a direct, tangible impact on how next-generation AI models are built, evaluated, and improvedPotential for ongoing work and contract extension as new projects launch