Systems Software Engineer - Machine Learning Ops

Systems Software Engineer — Machine Learning Ops (AI Infrastructure)

About the Role

What if your C++ expertise could directly shape the infrastructure powering the next generation of AI models? We're looking for seasoned systems engineers to build, optimize, and scale the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on every day.

This is a fully remote, flexible contract role for senior engineers who want to work on real production systems at the cutting edge of AI development — not toy projects, not demos. The work is high-impact, technically demanding, and genuinely matters.

• 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 existing C++ codebases used in production ML environments
• Collaborate with research, data, and engineering teams to support model training and evaluation infrastructure
• Identify bottlenecks and edge cases in system and data behavior, and implement robust, scalable solutions
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

Who You Are

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

Nice to Have

• Prior experience with data annotation, data quality pipelines, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience building distributed systems or developer tooling
• Background in research computing or high-performance computing environments

Why Join Us

• Work directly with leading AI labs on production systems that shape the future of AI
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the substance and structure of serious engineering work
• Contribute to infrastructure that powers real model training and evaluation at scale
• Potential for ongoing work and contract extension as projects grow and evolve