Live opening · Posted 7 days ago
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About The Role
What if your Python expertise could directly shape the data pipelines and evaluation systems powering the world's most advanced AI models? We're looking for Senior Python Full-Stack Engineers to design and build the critical infrastructure that leading AI labs depend on — from high-performance data annotation tooling to scalable evaluation workflows.
This is a fully remote, flexible contract role with serious technical depth and real production impact. If you've spent years writing Python that actually ships and scales, this is where that experience pays off.
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 evaluation workflows
Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
Improve reliability, performance, and safety across production Python codebases
Collaborate with data, research, and engineering teams to support model training and evaluation workflows
Identify bottlenecks and edge cases in data and system behavior — then implement scalable, lasting fixes
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
Experienced full-stack developer with a strong systems programming background
5+ years of professional experience writing production-grade Python
Deep understanding of performance optimization and concurrency — asyncio, multiprocessing, threading
Comfortable with type safety tooling such as Pydantic and mypy
Proven track record building robust backend services (FastAPI, Django) or scalable data pipelines
Able to commit 20–40 hours per week with reliability and professionalism
Nice to Have
Prior experience with data annotation, 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 directly with research or ML engineering teams
Why Join Us
Work on real production systems alongside leading AI research labs
Fully remote and flexible — structure your hours around your life
Freelance autonomy with the substance and challenge of high-impact technical work
Make a direct, measurable contribution to the infrastructure powering next-generation AI
Potential for ongoing work and contract extension as new projects launch
Work arrangement
Yes
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