Principal Python Engineer — ML Infrastructure

Job summary

Design, build, and optimize high-performance Python systems, data pipelines, annotation tools, backend services, and evaluation workflows for AI training. Improve production reliability, performance, and safety; resolve system bottlenecks; and guide architecture decisions in collaboration with research, data, and engineering teams.

Job details

Principal Python Engineer — ML Infrastructure (AI Training) About The Role What if your Python expertise could directly shape the infrastructure that powers the most advanced AI systems in the world? We're looking for a Principal Python Engineer in Toronto to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — real production work with real impact at scale. This is a fully remote, flexible contract role for a seasoned engineer who thrives in high-performance, distributed environments and wants to work on problems that matter. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 20–40 hours/week What You'll Do Design, build, and optimize high-performance Python systems that power 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 production Python codebases Identify bottlenecks and edge cases in data and system behavior — then implement scalable, elegant fixes Collaborate with data, research, and engineering teams to support model training and evaluation workflows Drive architectural and system design decisions through synchronous technical reviews Who You Are Native or fluent English speaker with strong written and verbal communication skills Senior full-stack developer with a strong systems programming background 5+ years of professional experience writing production Python for large-scale infrastructure or platform engineering Deep expertise in designing distributed computing systems and managing concurrency with advanced asynchronous patterns Intimately familiar with Python internals — GIL limitations, memory profiling, and performance optimization for compute-heavy workloads Able to drive technical strategy and architectural decisions clearly and confidently Available to commit 20–40 hours per week Nice to Have Prior experience with data annotation, data quality, or model evaluation systems Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure Experience with distributed systems architecture or internal developer tooling Why Join Us Work directly with leading AI research labs on production systems that shape next-generation models Fully remote and flexible — structure your work around your life, not the other way around Freelance autonomy with the substance of high-impact, technically demanding work Collaborate with top engineers and researchers on problems at the frontier of AI infrastructure Potential for ongoing engagement and expanded scope as projects grow

What you’ll do

Design, build, and optimize high-performance Python systems, data pipelines, annotation tools, backend services, and evaluation workflows for AI training. Improve production reliability, performance, and safety; resolve system bottlenecks; and guide architecture decisions in collaboration with research, data, and engineering teams.

Requirements

Requires at least five years of professional Python experience in large-scale infrastructure or platform engineering, along with strong full-stack and systems programming experience. Candidates should have deep expertise in distributed computing, advanced asynchronous concurrency, Python internals, performance optimization, and technical leadership, and be available for 20–40 hours per week.

Benefits

• Flexible Schedule
• Remote Work
• Freelance Autonomy
• Potential for Ongoing Engagement

Listed skills

• Data Validation · Preferred
• Quality Control · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• Distributed Computing
• Asynchronous Programming
• Concurrency
• Python Internals
• Performance Optimization
• Memory Profiling
• AI Data Pipelines
• Data Annotation
• Data Validation
• Quality Control
• Model Evaluation
• Backend Development
• Full-Stack Development
• System Architecture
• Technical Communication

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Science & Research

More jobs from Alignerr