Principal Python Engineer - ML Infrastructure

Principal Python Engineer — ML Infrastructure (AI Training)About The RoleWhat if your deep Python expertise could directly shape the infrastructure behind the world's most advanced AI systems? 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 next-generation models.This is a fully remote, high-impact contract role for a seasoned engineer who thrives at the intersection of systems programming, distributed computing, and AI infrastructure. If you've spent years building production-grade Python at scale and want your work to matter at the frontier of AI — this is it.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 20–40 hours/weekWhat You'll DoDesign, build, and optimize high-performance Python systems supporting AI data pipelines and model evaluation workflowsDevelop full-stack tooling and backend services for large-scale data annotation, validation, and quality controlImprove reliability, performance, and safety across production Python codebases used by top AI research teamsCollaborate with data, research, and engineering teams to accelerate model training and evaluation workflowsIdentify bottlenecks and edge cases in data and system behavior — then implement scalable, lasting fixesDrive architectural decisions through synchronous design reviews with senior technical stakeholdersWho You AreNative or fluent English speaker with strong written and verbal communication skillsFull-stack developer with a deep systems programming foundation and 5+ years writing production Python for large-scale infrastructure or platform engineeringExpert in distributed computing systems and advanced asynchronous concurrency patternsDeep understanding of Python internals — GIL limitations, memory profiling, and compute-heavy performance optimizationComfortable driving technical strategy and architectural decisions independentlyAvailable to commit 20–40 hours per week on a consistent basisNice to HavePrior experience with data annotation, data quality systems, or model evaluation pipelinesFamiliarity with AI/ML workflows, model training, or benchmarking infrastructureBackground in distributed systems design or developer toolingWhy Join UsWork directly with leading AI research labs on real production systems at the frontier of AI developmentFully remote and flexible — work from anywhere on a schedule that fits your lifeFreelance autonomy with the structure and focus of meaningful, high-stakes engineering workMake a direct, tangible impact on the infrastructure powering the next generation of AIPotential for ongoing engagement and expanded scope as projects evolve