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
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