What are the responsibilities and job description for the Data Platform Engineer (Python) position at Alignerr?
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.
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
- 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
- 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
- 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
- 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
Salary : $50 - $75