Principal Python Engineer - ML Infrastructure

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

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.

Responsibilities

• 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.

Requirements

• 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.

Why Join Us

• 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.