Principal Python Engineer - ML Infrastructure

Principal Python Engineer — ML Infrastructure (AI Training)
About The Role
What 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: 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 evaluation workflows
Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
Improve reliability, performance, and safety across existing production Python codebases
Identify and resolve bottlenecks and edge cases in data and system behavior with scalable, well-engineered fixes
Collaborate with data, research, and engineering teams to support model training and evaluation workflows
Participate in synchronous design reviews to drive technical strategy and architectural decisions
Who You Are
Native or fluent English speaker with clear written and verbal communication skills
5+ years of professional experience writing production Python — specifically for large-scale infrastructure or platform engineering
Deep expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns
Strong command of Python internals — GIL limitations, memory profiling, and performance optimization for compute-heavy workloads
Full-stack development background with a strong systems programming foundation
Experienced driving technical strategy and contributing to architectural decisions at a senior or principal level
Able to commit 20–40 hours per week consistently
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 or developer tooling
Experience working directly with or adjacent to AI research teams
Why Join Us
Work on real production systems alongside the world's leading AI labs — this is infrastructure that actually ships
Fully remote and flexible — work on your own schedule from anywhere
Freelance autonomy with the depth and complexity of principal-level engineering work
Make a direct, tangible impact on how next-generation AI models are built, evaluated, and improved
Potential for ongoing work and contract extension as new projects launch

Work arrangement
Yes