Data Platform Engineer (Python)

Alignerr Corp.; New York (NY); Remote; USD 83,000 - 131,000; Full time

Job summary

Alignerr is seeking a Senior Python Full-Stack Engineer to design and optimize data pipelines, annotation tooling, and evaluation systems powering AI model training. This is a fully remote contract role embedded with data, research, and engineering teams.

You will build high-performance Python systems, develop backend services for data annotation and quality control, and collaborate on architecture decisions to scale production workloads.

Qualifications

• 5+ years of experience writing production-grade Python for data engineering
• Strong full-stack developer background with solid systems programming fundamentals
• Proficient with workflow orchestration tools for managing complex dependency graphs
• Experienced with dataframe processing libraries and cloud data warehouse SDKs
• Able to commit reliably to 20–40 hours per week

Responsibilities

• Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for data annotation, validation, and quality control
• Identify and fix bottlenecks, edge cases, and reliability issues across production Python codebases
• Collaborate directly with data, research, and engineering teams to support model training and benchmarking
• Participate in synchronous design reviews to iterate on architecture and implementation decisions
• Improve performance, safety, and scalability across existing infrastructure

Skills

Python

Data pipelines

Full-stack

Systems programming

Workflow orchestration

Dataframe processing

Cloud data warehouses

Tools

Pandas

Airflow

Snowflake

BigQuery

Job description

About The Role

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

This is a fully remote contract role working on real production systems — not toy projects. You'll be embedded alongside data, research, and engineering teams doing meaningful, high-visibility work at the frontier 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 large-scale AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for data annotation, validation, and quality control
• Identify and fix bottlenecks, edge cases, and reliability issues across production Python codebases
• Collaborate directly with data, research, and engineering teams to support model training and benchmarking
• Participate in synchronous design reviews to iterate on architecture and implementation decisions
• Improve performance, safety, and scalability across existing infrastructure

Who You Are

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

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 on cutting-edge AI projects alongside leading research labs at the frontier of the field
• Fully remote and flexible — work from wherever you do your best thinking
• Freelance autonomy with the structure and consistency of meaningful, ongoing technical work
• Make a direct, tangible impact on the systems that shape how AI models learn and improve
• Potential for extended engagement and expanded scope as projects evolve