Data Platform Engineer (Python)
Role summary
Alignerr is seeking a Senior Python Full-Stack Engineer specializing in AI Data & Infrastructure for a remote, contract role. The engineer will design, build, and optimize high-performance Python systems for AI data pipelines and evaluation workflows. Responsibilities include developing full-stack tooling for data annotation, validation, and quality control, improving system reliability and performance, and collaborating with cross-functional teams. The role requires 5+ years of production Python experience in data engineering, proficiency with workflow orchestration, and strong experience with data frame processing and cloud data warehouses via Python SDKs. Familiarity with AI/ML workflows and distributed systems is preferred.
About The Job
Alignerr
connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. We work on real production systems and high-impact research workflows across data, tooling, and infrastructure.
**Position**
Senior Python Full-Stack Engineer — AI Data & Infrastructure
Type:
Contract, Remote
Commitment:
20–40 hours/week
Compensation:
Competitive, hourly (based on experience)
**Role Responsibilities**
- Design, build, and optimize high-performance systems in Python 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 fixes
- Participate in synchronous reviews to iterate on system design and implementation decisions
Qualifications
Must-Have
- Native or fluent English speaker
- Full-stack developer experience with a strong systems programming background
- 5+ years of professional experience writing production Python for data engineering.
- Proficiency with workflow orchestration tools to manage complex dependency graphs.
- Strong experience with data frame processing libraries and interacting with cloud data warehouses via Python SDKs.
- Clear written and verbal communication skills.
- Ability to commit 20–40 hours per week.
Preferred
- 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
**Application Process**
- Submit your resume
- Complete a short technical screening
- Project matching and onboarding