Principal Python Engineer — ML Infrastructure (AI Training) About The Role What 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: Alignerr Type: Hourly Contract Location: Remote Commitment: 20–40 hours/week

What You'll Do

Design, build, and optimize high-performance Python systems supporting AI data pipelines and model evaluation workflows Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control Improve reliability, performance, and safety across production Python codebases used by top AI research teams Collaborate with data, research, and engineering teams to accelerate model training and evaluation workflows Identify bottlenecks and edge cases in data and system behavior — then implement scalable, lasting fixes Drive architectural decisions through synchronous design reviews with senior technical stakeholders Who You Are Native or fluent English speaker with strong written and verbal communication skills Full-stack developer with a deep systems programming foundation and 5+ years writing production Python for large-scale infrastructure or platform engineering Expert in distributed computing systems and advanced asynchronous concurrency patterns Deep understanding of Python internals — GIL limitations, memory profiling, and compute-heavy performance optimization Comfortable driving technical strategy and architectural decisions independently Available to commit 20–40 hours per week on a consistent basis

Nice to Have

Prior experience with data annotation, data quality systems, or model evaluation pipelines Familiarity with AI/ML workflows, model training, or benchmarking infrastructure Background in distributed systems design or developer tooling

Why Join Us

Work directly with leading AI research labs on real production systems at the frontier of AI development Fully remote and flexible — work from anywhere on a schedule that fits your life Freelance autonomy with the structure and focus of meaningful, high-stakes engineering work Make a direct, tangible impact on the infrastructure powering the next generation of AI Potential for ongoing engagement and expanded scope as projects evolve