Senior Python Full-Stack Engineer — AI Data & Infrastructure

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