Systems Software Engineer - Machine Learning Ops

Job Description

Design, build, and optimize high-performance C++ systems, data pipelines, annotation tools, and backend services for AI training and evaluation workflows. Improve production system reliability, performance, and correctness, and collaborate with research and engineering teams to identify and resolve bottlenecks and failures.

Requirements: Requires fluent English communication, a strong systems programming foundation, at least five years of professional production-grade C++ experience, and hands-on experience with ML framework frontends or inference runtimes. Candidates should also have experience with hardware acceleration APIs and be available for 20–40 hours per week; data annotation, evaluation infrastructure, distributed systems, and ML research experience are advantageous.

Key Skills: C++, Systems Programming, Machine Learning Operations, AI Infrastructure, Data Pipelines, Full-Stack Development, Backend Services, Data Annotation, Data Validation, Quality Control, ML Frameworks, Inference Runtimes, Hardware Acceleration, Distributed Systems, Model Training, Benchmarking

Benefits: Fully Remote Work, Freelance Flexibility, Potential for Extended Engagement