Data Platform Engineer (Python)

Data Platform Engineer (Python)

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

This is a fully remote, flexible contract role for an experienced engineer who thrives on high-impact, technically challenging work. If you've spent years building production Python systems and want to apply that experience at the frontier of AI development — this is the role.

• 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-ready fixes
• Participate in synchronous design reviews to iterate on system architecture and implementation decisions

• 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 to manage complex dependency graphs
• Experienced with dataframe processing libraries and cloud data warehouse SDKs in Python
• Self-directed and reliable — able to commit 20–40 hours per week and deliver consistently

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

• Work on real production systems used by leading AI research labs
• Fully remote and async-friendly — work from wherever you do your best work
• Freelance autonomy with the structure and consistency of ongoing project-based work
• Make a tangible impact on the infrastructure powering next-generation AI models
• Potential for extended engagement and additional projects as the work evolves