Systems Software Engineer - Machine Learning Ops

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