AI Summary
Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and model evaluation workflows. Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation cycles. Drive architectural decisions through synchronous design reviews and clear technical communication.
Key Highlights
Design, build, and optimize high-performance Python systems
Collaborate with data, research, and engineering teams
Drive architectural decisions through design reviews
Key Responsibilities
Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and model evaluation workflows
Develop full-stack backend tooling and services for data annotation, validation, and quality control at scale
Diagnose and resolve bottlenecks across compute-heavy, distributed systems using advanced async patterns and profiling techniques
Improve reliability, safety, and performance across existing production Python codebases
Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation cycles
Drive architectural decisions through synchronous design reviews and clear technical communication
Technical Skills Required
Benefits & Perks
Fully remote and flexible
Freelance autonomy
Potential for ongoing work and contract extension
Nice to Have
Prior experience with data annotation, data quality, or evaluation systems
Familiarity with AI/ML workflows, model training, or benchmarking pipelines
Background in distributed systems architecture or developer tooling
Job Description
Principal Python Engineer — ML Infrastructure (AI Training)
About The Role
What if your Python expertise could directly shape the infrastructure powering some of the world's most advanced AI systems? We're looking for a Principal Python Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — working on real production code with meaningful, measurable impact.
This is a fully remote, flexible contract role for a senior engineer who thrives at the intersection of systems programming, distributed computing, and AI infrastructure.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
- Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and model evaluation workflows
- Develop full-stack backend tooling and services for data annotation, validation, and quality control at scale
- Diagnose and resolve bottlenecks across compute-heavy, distributed systems using advanced async patterns and profiling techniques
- Improve reliability, safety, and performance across existing production Python codebases
- Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation cycles
- Drive architectural decisions through synchronous design reviews and clear technical communication
Interested in remote work opportunities in Development & Programming? Discover Development & Programming Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- 5+ years writing production Python for large-scale infrastructure or platform engineering
- Deep expertise in distributed computing, concurrency, and advanced asynchronous programming patterns
- Fluent in Python internals — including GIL limitations, memory profiling, and performance optimization for compute-heavy workloads
- Experienced full-stack developer with a strong systems programming background
- Clear, confident communicator capable of driving technical strategy and architectural decisions
- Native or fluent English speaker
- Available to commit 20–40 hours per week
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Prior experience with data annotation, data quality, or evaluation systems
- Familiarity with AI/ML workflows, model training, or benchmarking pipelines
- Background in distributed systems architecture or developer tooling
- Exposure to working directly with AI research teams or labs
- Work on real, high-impact production systems used by leading AI research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the depth and structure of meaningful, long-term technical work
- Collaborate with top engineers and researchers at the frontier of AI development
- Potential for ongoing work and contract extension as new projects launch
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