Data Platform Engineer (Python)
About this role
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
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