Principal Python Engineer — ML Infrastructure
About this role
About the Role What if your Python expertise could directly shape the infrastructure that powers the most advanced AI systems in the world? We're looking for a Principal Python Engineer in São Paulo to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — real production work with real impact at scale. This is a fully remote, flexible contract role for a seasoned engineer who thrives in high-performance, distributed environments and wants to work on problems that genuinely matter. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 20–40 hours/week What You'll Do - Design, build, and optimize high-performance Python systems that power AI data pipelines and 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 - Identify bottlenecks and edge cases in data and system behavior — then implement scalable, elegant fixes - Collaborate with data, research, and engineering teams to support model training and evaluation workflows - Drive architectural and system design decisions through synchronous technical reviews Who You Are - Fluent English speaker with strong written and verbal communication skills - Senior full-stack developer with a strong systems programming background - 5+ years of professional experience writing production Python for large-scale infrastructure or platform engineering - Deep expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns - Intimately familiar with Python internals — GIL limitations, memory profiling, and performance optimization for compute-heavy workloads - Able to drive technical strategy and architectural decisions clearly and confidently - Available to commit 20–40 hours per week Nice to Have - Prior experience with data annotation, data quality, or model evaluation systems - Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure - Experience with distributed systems architecture or internal developer tooling Why Join Us - Work directly with leading AI research labs on production systems that shape next-generation models - Fully remote and flexible — structure your work around your life, not the other way around - Freelance autonomy with the substance of high-impact, technically demanding work - Collaborate with top engineers and researchers on problems at the frontier of AI infrastructure - Potential for ongoing engagement and expanded scope as projects grow
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