Data Platform Engineer (Python)

Alignerr; Denver (CO); Remote; USD 55,000 - 110,000; Full time

Job summary

Alignerr is seeking a Senior Python Full-Stack Engineer to design and build data pipelines, annotation tooling, and evaluation infrastructure powering AI model training and evaluation. This is a fully remote hourly contract for 20–40 hours per week, offering flexibility and real production impact.

You will design high-performance Python systems, develop tooling for data annotation and QC, and collaborate with data scientists and engineers to optimize workflows, reliability, and scalability in

Qualifications

• 5+ years of professional experience writing production Python for data engineering.
• Proficient with workflow orchestration tools for managing complex dependency graphs.
• Experienced with dataframe processing libraries and cloud data warehouse integrations via Python SDKs.

Responsibilities

• Design, build, and optimize high-performance Python systems supporting 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 existing Python codebases.
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows.

Skills

Python

Data engineering

Orchestration tools

Dataframes

Cloud SDKs

Job description

About The Role

What if your Python expertise could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for a Senior Python Full-Stack Engineer to design and build the data pipelines, annotation tooling, and evaluation infrastructure that leading AI labs depend on to train and improve next-generation models.

About The Role

What if your Python expertise could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for a Senior Python Full-Stack Engineer to design and build the data pipelines, annotation tooling, and evaluation infrastructure that leading AI labs depend on to train and improve next-generation models.

This is a fully remote, flexible contract role for experienced engineers who want to work on real production systems — not toy projects — at the cutting edge of AI development.

• 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 evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
• Improve reliability, performance, and safety across existing Python codebases
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Identify bottlenecks and edge cases in data and system behavior, and implement scalable, production-grade fixes
• Participate in synchronous design reviews to iterate on architecture and implementation decisions
  
  

Who You Are

• Native or fluent English speaker with clear written and verbal communication skills
• Full-stack developer with a strong systems programming background
• 5+ years of professional experience writing production Python for data engineering
• Proficient with workflow orchestration tools for managing complex dependency graphs
• Experienced with dataframe processing libraries and cloud data warehouse integrations via Python SDKs
• Able to commit 20–40 hours per week with reliability and consistency
  
  

Nice to Have

• Prior experience with data annotation, data quality pipelines, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
• Experience with distributed systems or developer tooling
  
  

Why Join Us

• Work directly with leading AI labs on systems that influence how next-generation models are built
• Fully remote and flexible — work from anywhere, on a schedule that suits you
• Tackle genuinely hard, high-impact engineering problems — not maintenance tickets
• Collaborate with a sharp, distributed team of engineers and researchers
• Potential for ongoing work and contract extension as new projects launch