Job Description

Systems Software Engineer — Machine Learning Ops

About The Role

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

This is a fully remote, flexible contract role for engineers who care about performance, reliability, and working on systems that genuinely matter. You'll be embedded in real production workflows alongside top-tier research and engineering teams.

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 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 correctness across existing C++ codebases
Collaborate with data, research, and engineering teams to support model training and evaluation at scale
Identify bottlenecks and edge cases in data and system behavior — then implement scalable, production-grade fixes
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 background
Experience 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 consistently

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 with distributed systems or developer tooling
Background in systems performance profiling and optimization

Why Join Us

Work on production systems that directly influence the capabilities of frontier AI models
Collaborate with engineers and researchers at leading AI labs
Fully remote and flexible — work when and where it suits you
Freelance autonomy with the structure and purpose of high-stakes engineering work
Potential for ongoing engagement and expanded scope as new projects launch

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