Python Software Engineer - AI Workflows
Indexed description
This is a fully remote, flexible contract role for an experienced engineer who wants to work on real production systems at the frontier of AI development — not toy projects, but high-impact infrastructure that matters.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
- Design, build, and optimize high-performance Python systems supporting AI data pipelines and evaluation workflows
- Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
- Improve reliability, performance, and robustness across existing Python codebases
- Collaborate with data, research, and engineering teams to support model training and evaluation
- Identify bottlenecks and edge cases in data and system behavior, and implement scalable, production-grade fixes
- Participate in synchronous design reviews and iterate on system architecture decisions
- 3–5+ years of professional experience writing production-grade Python
- Full-stack developer with a strong systems programming background
- Writes clean, maintainable code with proper use of linters, formatters, and testing frameworks
- Experienced integrating AI services and APIs, handling edge cases, and ensuring robust error reporting
- Clear and effective written and verbal communicator
- Native or fluent English speaker
- Able to commit 20–40 hours per week consistently
- 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 developer tooling at scale
- Work directly with leading AI research labs on production systems that matter
- Fully remote and flexible — work from wherever you do your best thinking
- Freelance autonomy with the structure and purpose of high-impact, technically challenging work
- Get hands-on experience at the cutting edge of AI infrastructure before it becomes mainstream
- Potential for ongoing work and contract extension as projects evolve and new ones launch
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