Backend Developer — Data Annotation Systems (AI Training)
About The Role
What if your Python expertise could directly shape the infrastructure that trains the world's most advanced AI models? We're looking for a Senior Python Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on every day.
This is a fully remote, flexible contract role for a seasoned engineer who wants to work on real production systems — not toy projects — alongside top-tier research and engineering teams.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
What You'll Do
- Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and model evaluation workflows
- Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
- Build and maintain asynchronous task queues to handle long-running background jobs reliably
- Optimize database queries for high-read/write workloads and serve data via real-time protocols including WebSockets
- Improve reliability, performance, and safety across existing production Python codebases
- Collaborate with data scientists, researchers, and engineers to support model training and evaluation workflows
- Identify bottlenecks and edge cases across data systems and implement scalable, production-grade fixes
- Participate in synchronous design and code reviews to drive sound architectural decisions
Who You Are
- 3–5+ years of professional experience writing production-grade Python
- Strong full-stack developer with a solid systems programming background
- Experienced building asynchronous task queues and background job systems
- Proficient in optimizing database queries for high-throughput applications
- Comfortable serving and consuming real-time data via WebSockets or similar protocols
- Clear, precise written and verbal communicator — you can articulate technical decisions well
- Native or fluent English speaker
- Able to commit 20–40 hours per week consistently
Nice to Have
- Prior experience with data annotation platforms, data quality systems, or model evaluation infrastructure
- Familiarity with AI/ML workflows, model training pipelines, or benchmarking systems
- Experience designing or maintaining distributed systems
- Background in developer tooling or internal platform engineering
Why Join Us
- Work on cutting-edge AI infrastructure alongside leading research labs — this is real, high-stakes work
- Fully remote and async-friendly — work from wherever you do your best thinking
- Freelance autonomy with the structure and consistency of meaningful, ongoing project work
- Make a direct, tangible impact on how next-generation AI models are built, trained, and evaluated
- Potential for ongoing work and contract extension as new projects and partnerships launch
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