About the Role
What if your Python engineering skills could directly shape how the world's most advanced AI models are built, tested, and improved? We're looking for a Senior Python Infrastructure Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that sit at the heart of cutting-edge AI research.
This is a fully remote, flexible contract role working alongside leading AI labs on real production infrastructure. If you're a seasoned Python engineer who wants meaningful, high-impact work — this is it.
- 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 AI data pipelines and model evaluation workflows
- Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
- Build and maintain evaluation harnesses for ML models, integrating with inference frameworks
- Improve reliability, performance, and safety across existing Python codebases
- Instrument systems with observability tooling and metrics collection to monitor reliability and model performance
- Identify bottlenecks and edge cases in data and system behavior, and implement scalable solutions
- Collaborate with data, research, and engineering teams to support model training and evaluation workflows
- 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 evaluation harnesses for ML models and integrating with inference frameworks
- Solid background in observability, metrics collection, and monitoring system reliability
- Self-directed and dependable — able to commit 20–40 hours per week and deliver consistently
Nice to Have
- Prior experience with data annotation, data quality pipelines, or evaluation systems
- Familiarity with AI/ML workflows, model training, or benchmarking pipelines
- Experience with distributed systems or developer tooling
- Background working directly with AI research teams or at AI-focused companies
Why Join Us
- Work on production systems powering some of the most advanced AI research in the world
- Fully remote and async-friendly — work from wherever you do your best thinking
- Freelance autonomy with the depth and structure of meaningful, long-term engineering work
- Collaborate directly with AI researchers and engineers at leading labs
- Potential for ongoing work and contract extension as new projects launch