Remote ML Ops Systems Engineer – High-Performance C++

Alignerr Corp.; New York (NY); Remote; USD 83,000 - 152,000; Part time

Job summary

Alignerr Corp. is seeking a Systems Software Engineer — Machine Learning Ops to design, build, and optimize high-performance C++ systems powering AI data pipelines and evaluation workflows.

This is a fully remote, hourly contract role for a seasoned engineer with deep C++ expertise who thrives on production-grade systems. You will develop tooling for large-scale data annotation and validation, improve reliability and safety of codebases, and collaborate with data, research, and engineering teams

Qualifications

• 5+ years of professional C++ production code experience.
• Strong systems programming background with C++ expertise.
• Experience with ML frameworks frontends or inference runtimes.
• Familiarity with hardware acceleration APIs for model inference.
• Able to commit 20–40 hours per week reliably.

Responsibilities

• Design, build, and optimize high-performance C++ systems 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 C++ codebases used in production AI environments.
• 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, maintainable fixes.
• Participate in synchronous design reviews to iterate on system architecture and implementation decisions.

Skills

C++ expert

Systems programming

ML frameworks frontends

Performance optimization

English fluency

Job description

Alignerr Corp. is seeking a Systems Software Engineer — Machine Learning Ops to design, build, and optimize high-performance C++ systems powering AI data pipelines and evaluation workflows.

This is a fully remote, hourly contract role for a seasoned engineer with deep C++ expertise who thrives on production-grade systems. You will develop tooling for large-scale data annotation and validation, improve reliability and safety of codebases, and collaborate with data, research, and engineering teams