Remote Systems Engineer — ML Ops & High-Performance C++

Alignerr Corp.; Seattle (WA); Remote; USD 83,000 - 152,000; Full time

Job summary

Alignerr is seeking a Systems Software Engineer — Machine Learning Ops to design and optimize high-performance C++ systems powering large-scale AI data pipelines and evaluation workflows. The role is fully remote as an hourly contract, demanding 20–40 hours per week with strong systems programming and ML tooling experience.

You will collaborate with data, research, and engineering teams to accelerate model training and evaluation, while improving reliability and performance across production

Qualifications

• 5+ years of professional experience writing production-grade C++.
• Strong systems programming background with full-stack capability.
• Experience with ML frameworks or inference runtimes frontends.
• Familiar with hardware acceleration APIs for optimizing model inference.
• Excellent English communication, written and spoken.
• Able to commit 20–40 hours per week reliably.

Responsibilities

• Design, build, and optimize high-performance C++ systems supporting large-scale AI data pipelines and evaluation workflows.
• Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale.
• Improve reliability, performance, and safety across production C++ codebases.
• Identify and resolve bottlenecks, edge cases, and systemic issues in data and system behavior.
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows.
• Participate in synchronous design reviews to iterate on architecture and implementation decisions.

Skills

C++

Systems programming

Full-stack development

English proficiency

ML frameworks frontends

Hardware acceleration

Job description

Alignerr is seeking a Systems Software Engineer — Machine Learning Ops to design and optimize high-performance C++ systems powering large-scale AI data pipelines and evaluation workflows. The role is fully remote as an hourly contract, demanding 20–40 hours per week with strong systems programming and ML tooling experience.

You will collaborate with data, research, and engineering teams to accelerate model training and evaluation, while improving reliability and performance across production