Principal Python Engineer - ML Infrastructure

Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. The role involves designing, building, and optimizing high-performance systems in Python to support AI data pipelines and evaluation workflows, along with developing full-stack tooling and backend services for data annotation and quality control.

Responsibilities:

• Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
• Improve reliability, performance, and safety across existing Python codebases
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Identify bottlenecks and edge cases in data and system behavior, and implement scalable fixes
• Participate in synchronous reviews to iterate on system design and implementation decisions

Requirements:

• Native or fluent English speaker
• Full-stack developer experience with a strong systems programming background
• 5+ years of professional experience writing production Python, specifically for large-scale infrastructure or platform engineering
• Expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns
• Deep understanding of Python internals (GIL limitations, memory profiling) and experience optimizing performance for compute-heavy workloads
• Clear written and verbal communication skills for driving technical strategy and architectural decisions
• Ability to commit 20–40 hours per week
• Prior experience with data annotation, data quality, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience with distributed systems or developer tooling