Data Platform Engineer (Python)

Data Platform Engineer (Python)

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, flexible contract role for an experienced engineer who wants meaningful, high-impact work 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, then implement scalable, production-ready 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-grade Python for data engineering
• Proficient with workflow orchestration tools for managing complex dependency graphs
• Experienced with dataframe processing libraries and cloud data warehouses via Python SDKs
• Self-directed and reliable — able to commit 20–40 hours per week consistently

Nice to Have

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

Why Join Us

• Work on production systems and high-impact workflows directly used by leading AI research labs
• Fully remote and flexible — work when and where you do your best work
• Freelance autonomy with the structure of real, meaningful engineering challenges
• Contribute to AI infrastructure that shapes the future of model development at scale
• Potential for ongoing work and contract extension as projects grow and evolve