Principal Python Engineer — ML Infrastructure

aitrainer

Deutschland

Vor Ort

EUR 70.000 - 90.000

Teilzeit

14 Tage+

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Benefits dieser Stelle

Flexible work hours
Remote work opportunity
Engagement with leading AI labs

Zusammenfassung

Aitrainer is seeking a Principal Python Engineer to shape advanced AI systems remotely. In this role, you'll design and build data pipelines and tooling for large-scale AI processes. Ideal candidates have 5+ years of experience in production Python, strong systems programming skills, and a passion for impactful work.

This position offers the flexibility of a freelance contract with substantial responsibilities, allowing you to structure work around your life while engaging in high-performance tasks with top AI research labs.

Qualifikationen

  • 5+ years of professional experience writing production Python for large-scale infrastructure.
  • Strong systems programming background and ability to drive technical strategy.
  • Fluent in English with strong communication skills.

Aufgaben

  • Design, build, and optimize high-performance Python systems.
  • Develop full-stack tooling and backend services for data annotation.
  • Collaborate with data, research, and engineering teams.

Kenntnisse

Python expertise
Distributed computing systems
Asynchronous patterns
Full-stack development

Jobbeschreibung

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 Austin 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 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
  • Native or 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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