Python Insfrastructure Engineer - Model Evaluation

Alignerr Corp.; New York (NY); Remote; USD 83,000 - 165,000; Full time

Job summary

Alignerr Corp. is seeking a Senior Python Infrastructure Engineer to design and build data pipelines, evaluation harnesses, and annotation tooling powering AI systems.

This is a fully remote hourly contract, requiring 20–40 hours per week, with work shipping to production and influencing model quality at scale.

Qualifications

• 3–5+ years writing production-grade Python.
• Full-stack developer with strong systems programming background.
• Experience building evaluation harnesses for ML models.
• Familiar with observability, metrics, and reliability.
• Available to commit 20–40 hours per week.

Responsibilities

• Design and optimize Python data pipelines and evaluation workflows.
• Develop tooling and backend services for large-scale data annotation and validation.
• Build evaluation harnesses that integrate with inference frameworks.
• Improve reliability, performance, and safety of Python codebases.
• Instrument systems with observability tooling and metrics collection.
• Identify bottlenecks and implement scalable fixes.
• Collaborate with data, research, and engineering teams during design reviews.

Skills

Python

Full-stack development

Observability

Metrics collection

System reliability

Communication

Tools

Inference frameworks

Data annotation tooling

Internal developer tooling

Job description

Python Infrastructure Engineer — Model Evaluation (AI Training)

About The Role

What if your Python expertise could directly shape how the world's most advanced AI models are built, evaluated, and improved? We're looking for a Senior Python Infrastructure Engineer to design and build the data pipelines, evaluation harnesses, and annotation tooling that power next-generation AI systems at leading research labs.

This is a fully remote contract role with serious technical depth — the kind of work that ships to production and influences model quality at scale.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

What You'll Do

• Design, build, and optimize high-performance Python systems supporting AI data pipelines and model evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
• Build and maintain evaluation harnesses that integrate with inference frameworks and benchmarking pipelines
• Improve reliability, performance, and safety across existing Python codebases
• Instrument systems with observability tooling and metrics collection to monitor model performance and system health
• Identify bottlenecks and edge cases in data and system behavior, and implement scalable, maintainable fixes
• Collaborate with data, research, and engineering teams through synchronous design reviews and async communication

Who You Are

• Native or fluent English speaker with clear written and verbal communication skills
• 3–5+ years of professional experience writing production-grade Python
• Full-stack developer with a strong systems programming background
• Experienced building evaluation harnesses for ML models and integrating with inference frameworks
• Strong grasp of observability, metrics collection, and system reliability practices
• Able to commit 20–40 hours per week with consistent availability

Nice to Have

• Prior experience with data annotation pipelines, data quality systems, or model evaluation infrastructure
• Familiarity with AI/ML workflows, model training, or benchmarking frameworks
• Experience with distributed systems or internal developer tooling
• Background working directly with AI labs or ML research teams

Why Join Us

• Work on real production systems at the frontier of AI development alongside leading research labs
• Fully remote and flexible — work from wherever you do your best work
• Freelance autonomy with the structure of high-impact, technically challenging projects
• Make a direct, measurable contribution to how next-generation AI models are evaluated and improved
• Potential for ongoing work and contract extension as new projects launch