Principal Python Engineer - ML Infrastructure

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