Backend Developer - Data Annotation Systems

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 build and optimize 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 with meaningful impact — not toy projects.

• 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 evaluation workflows
• Develop full-stack backend tooling and 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 such as WebSockets
• Improve reliability, performance, and robustness across existing Python codebases
• Identify bottlenecks and edge cases in data and system behavior, and implement scalable, production-ready fixes
• Collaborate closely with data, research, and engineering teams to support model training and evaluation workflows
• Participate in synchronous design reviews to iterate on system architecture and implementation decisions

• Strong full-stack developer with a solid systems programming background
• 3–5+ years of professional experience writing production-grade Python
• Experienced building asynchronous task queues for long-running background processing
• Proficient in optimizing database queries for high-throughput applications
• Comfortable working with real-time data protocols (e.g., WebSockets)
• Clear, precise written and verbal communicator
• Able to commit 20–40 hours per week consistently
• Native or fluent English speaker

• Prior experience with data annotation platforms, data quality systems, or evaluation pipelines
• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
• Experience with distributed systems or developer tooling
• Background working alongside research or data science teams

• Work directly with leading AI labs on production systems that matter
• Fully remote and flexible — work from anywhere on a schedule that suits you
• Freelance autonomy with the structure of high-quality, technically challenging work
• Contribute to AI infrastructure that influences how next-generation models are built and evaluated
• Potential for ongoing work and contract extension as new projects launch