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Systems Software Engineer - Machine Learning Ops
Job summary
Work model
About The Role
What if your systems engineering skills could directly shape the infrastructure powering the world's most advanced AI models? We're looking for a senior C++ engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and ship next-generation models.
This is a fully remote, flexible contract role for a seasoned engineer who knows C++ deeply and thrives working on high-impact, production-grade systems. If you've spent years writing performance-critical code and want to apply that expertise at the cutting edge of AI development, this is the role for you.
- 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 safety across existing C++ codebases used in production AI environments
- Collaborate with data, research, and engineering teams to support model training and evaluation workflows
- Identify bottlenecks and edge cases in data and system behavior, and implement scalable, maintainable fixes
- Participate in synchronous design reviews to iterate on system 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 and deep C++ expertise
- 5+ years of professional experience writing production C++ code
- 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 consistency and reliability
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 design or developer tooling
- Background in performance profiling, debugging, or systems reliability engineering
Why Join Us
- Work on real production systems used by leading AI research labs
- Fully remote and flexible --- work when and where it suits you
- Freelance autonomy with the structure of meaningful, impactful technical work
- Contribute directly to infrastructure that shapes the future of AI development
- Potential for ongoing work and contract extension as new projects launch