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Principal Python Engineer - ML Infrastructure
Remote / Online - Candidates ideally in
Seattle, King County, Washington, 98127, USA
Listed on 2025-12-27
Seattle, King County, Washington, 98127, USA
Listing for:
Labelbox
Remote/Work from Home
position Listed on 2025-12-27
Job specializations:
-
IT/Tech
AI Engineer, Data Engineer
Job Description & How to Apply Below
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.
PositionSenior Python Full‑Stack Engineer — AI Data & Infrastructure
Type: Contract, Remote
Commitment: 20–40 hours/week
Compensation: Competitive, hourly (based on experience). $50–$75 an hour
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
- 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, specifically for large‑scale infrastructure or platform engineering
- Expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns
- Deep understanding of Python internals (GIL limitations, memory profiling) and experience optimizing performance for compute‑heavy workloads
- Clear written and verbal communication skills for driving technical strategy and architectural decisions
- 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
- Submit your resume
- Complete a short technical screening
- Project matching and onboarding
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