Principal Python Engineer — ML Infrastructure

Alignerr Corp.; São Paulo; Remoto; BRL 460.000 - 920.000; Tempo integral

Benefícios oferecidos por esta vaga

Fully remote

Flexible schedule

Resumo da vaga

Alignerr is seeking a Principal Python Engineer to architect and build high-performance Python systems that power AI data pipelines and evaluation workflows. This fully remote, hourly-contract role suits a seasoned engineer who thrives in distributed environments and seeks real impact at scale.

You will design data annotation tooling, optimize backend services, and collaborate with data, research, and engineering teams to support model training and evaluation.

Qualificações

• 5+ years Python production experience in large-scale infra.
• Deep expertise in distributed systems design and asynchronous patterns.
• Able to drive technical strategy and architectural decisions.

Responsabilidades

• Design, build, and optimize high-performance Python systems powering data pipelines.
• Develop full-stack tooling and backend services for large-scale data annotation and quality control.
• Improve reliability, performance, and safety across production Python codebases.
• Identify bottlenecks and implement scalable fixes.
• Collaborate with data, research, and engineering teams for training and evaluation workflows.
• Drive architectural and system design decisions through technical reviews.

Conhecimentos

Python

Distributed systems

Asynchronous patterns

English

Descrição da vaga

Principal Python Engineer — ML Infrastructure (AI Training)

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.

Job Details

• 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