Systems Software Engineer - Machine Learning Ops

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