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Senior Python Full-Stack Engineer — AI Data & Infrastructure

Technology
Alignerr
Seattle, United StatesYesterdayUntil 6/14/2026
Contract

Job description

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 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 working on real production systems — not toy projects. If you're a seasoned Python engineer who thrives on high-impact, technically challenging work, this is where your skills belong.

  • 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 large-scale AI data pipelines and evaluation workflows
  • Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
  • Identify and eliminate bottlenecks, edge cases, and reliability issues across production codebases
  • Collaborate closely with data, research, and engineering teams to support model training and evaluation infrastructure
  • Improve safety, performance, and maintainability of existing systems
  • Participate in synchronous design reviews and iterate on system architecture with expert colleagues

Who You Are

  • Native or fluent English speaker with strong written and verbal communication skills
  • Full-stack developer with a solid systems programming background
  • 5+ years of professional experience writing production-grade Python
  • Deep understanding of performance optimization and concurrency — asyncio, multiprocessing, threading — and type safety tools like Pydantic and mypy
  • Proven experience building robust backend services (FastAPI, Django, or similar) or scalable data pipelines
  • Able to commit 20–40 hours per week with reliability and professionalism

Nice to Have

  • Prior experience with data annotation platforms, data quality workflows, or evaluation systems
  • Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure
  • Experience with distributed systems, developer tooling, or MLOps

Why Join Us

  • Work directly with leading AI research labs on systems that matter
  • Fully remote and flexible — structure your hours around your life
  • Freelance autonomy with the depth and consistency of meaningful, long-term technical work
  • Collaborate with a sharp, technically rigorous team on genuinely hard engineering problems
  • Potential for ongoing work and contract extension as projects scale

Keywords
monthsOfExperience: 60OCamlDjangoPythonIterationType safetyMaintainability

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