
Data Platform Engineer (Python)
Department:Data Engineer
Type:REMOTE
Region:USA
Location:Seattle, WA
Experience:Mid-Senior level
Estimated Salary:$100,000 - $150,000
Skills:
PYTHONDATA ENGINEERINGWORKFLOW ORCHESTRATIONDATAFRAME PROCESSINGCLOUD DATA WAREHOUSESBACKEND SERVICESFULL-STACK DEVELOPMENT
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Job Description
Posted on: May 27, 2026
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
Originally posted on LinkedIn
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