Principal Python Engineer — ML Infrastructure (AI Training) About the Role What if your Python expertise could directly shape the infrastructure that powers the most advanced AI systems in the world?
Principal Python Engineer — ML Infrastructure
Job description
Principal Python Engineer — ML Infrastructure (AI Training)
About the Role
What if your Python expertise could directly shape the infrastructure that powers the most advanced AI systems in the world? We're looking for a Principal Python Engineer in São Paulo to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — real production work with real impact at scale.
This is a fully remote, flexible contract role for a seasoned engineer who thrives in high-performance, distributed environments and wants to work on problems that genuinely matter.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
What You'll Do
- Design, build, and optimize high-performance Python systems that power 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
- Identify bottlenecks and edge cases in data and system behavior — then implement scalable, elegant fixes
- Collaborate with data, research, and engineering teams to support model training and evaluation workflows
- Drive architectural and system design decisions through synchronous technical reviews
Who You Are
- Fluent English speaker with strong written and verbal communication skills
- Senior full-stack developer with a strong systems programming background
- 5+ years of professional experience writing production Python for large-scale infrastructure or platform engineering
- Deep expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns
- Intimately familiar with Python internals — GIL limitations, memory profiling, and performance optimization for compute-heavy workloads
- Able to drive technical strategy and architectural decisions clearly and confidently
- Available to commit 20–40 hours per week
Nice to Have
- Prior experience with data annotation, data quality, or model evaluation systems
- Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure
- Experience with distributed systems architecture or internal developer tooling
Why Join Us
- Work directly with leading AI research labs on production systems that shape next-generation models
- Fully remote and flexible — structure your work around your life, not the other way around
- Freelance autonomy with the substance of high-impact, technically demanding work
- Collaborate with top engineers and researchers on problems at the frontier of AI infrastructure
- Potential for ongoing engagement and expanded scope as projects grow
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