Senior Python Engineer — ML Infrastructure (Remote Contract)

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

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.