Principal Python Engineer - ML Infrastructure
About this role
About the Role What if your Python expertise could directly shape the infrastructure powering some of the world's most advanced AI systems? We're looking for a Principal Python Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — working on real production code with meaningful, measurable impact. This is a fully remote, flexible contract role for a senior engineer who thrives at the intersection of systems programming, distributed computing, and AI infrastructure. - 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 backend tooling and services for data annotation, validation, and quality control at scale - Diagnose and resolve bottlenecks across compute-heavy, distributed systems using advanced async patterns and profiling techniques - Improve reliability, safety, and performance across existing production Python codebases - Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation cycles - Drive architectural decisions through synchronous design reviews and clear technical communication Who You Are - 5+ years writing production Python for large-scale infrastructure or platform engineering - Deep expertise in distributed computing, concurrency, and advanced asynchronous programming patterns - Fluent in Python internals — including GIL limitations, memory profiling, and performance optimization for compute-heavy workloads - Experienced full-stack developer with a strong systems programming background - Clear, confident communicator capable of driving technical strategy and architectural decisions - Native or fluent English speaker - Available to commit 20–40 hours per week Nice to Have - Prior experience with data annotation, data quality, or evaluation systems - Familiarity with AI/ML workflows, model training, or benchmarking pipelines - Background in distributed systems architecture or developer tooling - Exposure to working directly with AI research teams or labs Why Join Us - Work on real, high-impact production systems used by leading AI research labs - Fully remote and flexible — work when and where it suits you - Freelance autonomy with the depth and structure of meaningful, long-term technical work - Collaborate with top engineers and researchers at the frontier of AI development - Potential for ongoing work and contract extension as new projects launch
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