Data Platform Engineer (Python)

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

• 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

• 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

• 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

• 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