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