Principal Python Engineer — ML Infrastructure

Alignerr Corp.; Amsterdam; Remote; EUR 98,000 - 172,000; Full time

Benefits offered by this job

Remote work

Job summary

Alignerr Corp. is seeking a Principal Python Engineer — ML Infrastructure (AI Training) to design data pipelines, annotation tooling, and evaluation systems for production AI workloads. The role is fully remote as an hourly contract, with 20–40 hours per week and close collaboration with data, research, and engineering teams.

You will work in a high-performance distributed environment, shaping scalable Python infrastructure that powers model training and evaluation across AI labs.

Qualifications

• 5+ years of professional experience writing production Python for large-scale infrastructure or platform engineering.
• Senior full-stack developer with a strong systems programming background.
• Fluent English speaker with strong written and verbal communication skills.

Responsibilities

• 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.

Skills

Python

Distributed systems

Asynchronous programming

Performance optimization

System design

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 Amsterdam 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

• 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