Principal Python Engineer - ML Infrastructure

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