Backend Developer - Data Annotation Systems

October 16, 2026

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Backend Developer — Data Annotation Systems (AI Training) About The Role What if your Python expertise could directly shape the infrastructure behind the most advanced AI systems in the world? 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 thrives on high-impact systems work and wants to be close to the frontier of AI development. <ul><li>Organization: Alignerr</li><li>Type: Hourly Contract</li><li>Location: Remote</li><li>Commitment: 20–40 hours/week </li></ul>What You'll Do <ul><li>Design, build, and optimize high-performance Python systems that power AI data pipelines and model evaluation workflows</li><li>Develop full-stack backend services and tooling for large-scale data annotation, validation, and quality control</li><li>Build and maintain asynchronous task queues to handle complex, long-running background jobs at scale</li><li>Optimize database queries for high-read/write workloads and serve data via real-time protocols such as WebSockets</li><li>Improve reliability, performance, and safety across existing Python codebases</li><li>Collaborate closely with data, research, and engineering teams to support model training and evaluation workflows</li><li>Identify bottlenecks and edge cases in system and data behavior, then implement scalable, production-ready fixes</li><li>Participate in synchronous design reviews to iterate on architecture and implementation decisions </li></ul>Who You Are <ul><li>Native or fluent English speaker with clear written and verbal communication skills</li><li>Full-stack developer with a strong systems programming background and 3–5+ years of professional Python experience</li><li>Proven experience building and shipping production-grade Python applications</li><li>Experienced with asynchronous task queues and background job processing</li><li>Skilled at optimizing database performance for demanding, high-throughput applications</li><li>Comfortable working with real-time data protocols (e.g., WebSockets)</li><li>Self-directed and reliable — able to commit 20–40 hours per week and deliver consistently without hand-holding </li></ul>Nice to Have <ul><li>Prior experience with data annotation, data quality pipelines, or model evaluation infrastructure</li><li>Familiarity with AI/ML workflows, model training, or benchmarking systems</li><li>Experience with distributed systems, developer tooling, or data engineering </li></ul>Why Join Us <ul><li>Work directly with leading AI labs on production systems that matter</li><li>Fully remote and flexible — structure your work around your schedule</li><li>Freelance autonomy with the substance of high-impact engineering work</li><li>Get hands-on exposure to the cutting edge of AI infrastructure and research workflows</li><li>Potential for ongoing work and contract extension as projects scale</li></ul>

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