Principal Python Engineer - ML Infrastructure

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