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
What You'll Do
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
Who You Are
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
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
Exposure to working directly with AI research teams or labs
Why Join Us
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