Principal Python Engineer - ML Infrastructure

What You'll Do

• Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and model evaluation workflows
• Develop full-stack backend tooling and services for data annotation, validation, and quality control at scale
• Diagnose and resolve bottlenecks across compute-heavy, distributed systems using advanced async patterns and profiling techniques
• Improve reliability, safety, and performance across existing production Python codebases
• Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation cycles
• Drive architectural decisions through synchronous design reviews and clear technical communication

Who You Are

• 5+ years writing production Python for large-scale infrastructure or platform engineering
• Deep expertise in distributed computing, concurrency, and advanced asynchronous programming patterns
• Fluent in Python internals — including GIL limitations, memory profiling, and performance optimization for compute-heavy workloads
• Experienced full-stack developer with a strong systems programming background
• Clear, confident communicator capable of driving technical strategy and architectural decisions
• Native or fluent English speaker
• Available to commit 20–40 hours per week

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 architecture or developer tooling
• Exposure to working directly with AI research teams or labs