Systems Software Engineer - Machine Learning Ops

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

Systems Software Engineer — Machine Learning Ops

About The Role

What if your deep C++ expertise could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for a senior systems engineer to build and optimize the data pipelines, annotation tooling, and evaluation infrastructure that leading AI labs depend on to train and ship better models.

This is a fully remote, flexible contract role for engineers who thrive at the intersection of systems programming and cutting-edge AI. Real production systems. High-impact work. Serious technical depth.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

What You'll Do

• 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

Who You Are

• Native or fluent English speaker with clear written and verbal communication skills
• Full-stack developer with a strong systems programming background
• 5+ years of professional experience writing production-grade C++
• Experienced working with the C++ frontends of ML frameworks or inference runtimes
• Familiar with hardware acceleration APIs for optimizing model inference
• Able to commit 20–40 hours per week with reliability and consistency

Nice to Have

• Prior experience with data annotation, data quality, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience with distributed systems or developer tooling

Why Join Us

• Work directly on cutting-edge AI infrastructure alongside leading research labs
• Fully remote and flexible — work when and where you do your best work
• Freelance autonomy with the substance of high-impact, technically demanding projects
• Contribute to systems that meaningfully shape how next-generation AI models are built and evaluated
• Potential for ongoing work and contract extension as new projects launch