Principal Python Engineer - ML Infrastructure

About The Role

What if your Python expertise could directly shape the infrastructure powering some of the world's most advanced AI systems? We're looking for a Principal Python Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — working on real production code with meaningful, measurable impact.

This is a fully remote, flexible contract role for a senior engineer who thrives at the intersection of systems programming, distributed computing, and AI infrastructure.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

• 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

• 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

• 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

• Work on real, high-impact production systems used by leading AI research labs
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the depth and structure of meaningful, long-term technical work
• Collaborate with top engineers and researchers at the frontier of AI development
• Potential for ongoing work and contract extension as new projects launch