Backend Developer - Data Annotation Systems

Backend Developer — Data Annotation Systems (AI Infrastructure)

About The Role

What if your Python expertise could directly shape the infrastructure behind the world's most advanced AI models? We're looking for a Senior Python Full-Stack Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve next-generation models.

This is a fully remote, flexible contract role for an experienced engineer who wants to work on real production systems at the cutting edge of AI development — not toy projects, but infrastructure that matters.

• Organization: Alignerr

• Type: Hourly Contract

• Location: Remote

• Commitment: 20–40 hours/week

What You'll Do

• Design, build, and optimize high-performance Python systems that support large-scale AI data pipelines and evaluation workflows

• Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale

• Improve the reliability, performance, and safety of existing Python codebases

• Collaborate with data, research, and engineering teams to support model training and evaluation infrastructure

• Identify bottlenecks and edge cases in data and system behavior — then implement scalable, production-ready fixes

• Participate in synchronous design reviews to iterate on architecture and implementation decisions

Who You Are

• Native or fluent English speaker with clear written and verbal communication skills

• Full-stack developer with a strong systems programming background

• 3–5+ years of professional experience writing production-grade Python

• Experienced building asynchronous task queues for long-running background jobs

• Proficient in optimizing database queries for high-read/write workloads and serving data via real-time protocols (e.g., WebSockets)

• Able to commit 20–40 hours per week with reliability and consistency

Nice to Have

• Prior experience with data annotation, data quality pipelines, or evaluation systems

• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure

• Experience with distributed systems or internal developer tooling

Why Join Us

• Work directly with leading AI research labs on production-grade, high-impact systems

• Fully remote and flexible — work from anywhere on a schedule that suits you

• Freelance autonomy with the structure and focus of meaningful, substantive engineering work

• Make a direct, tangible contribution to the infrastructure shaping the future of AI

• Potential for ongoing work and contract extension as new projects launch