Systems Software Engineer - Machine Learning Ops

Job Description

Design, build, and optimize high-performance C++ systems, data pipelines, annotation tools, backend services, and evaluation infrastructure for AI model training and evaluation. Improve reliability, performance, and correctness by identifying bottlenecks and implementing scalable fixes in collaboration with research, data, and engineering teams.

Requirements: Candidates need at least five years of professional experience writing production-grade C++ and a strong systems programming background, along with full-stack development experience. They should have experience with C++ frontends for machine learning frameworks or inference runtimes, familiarity with hardware acceleration APIs, fluent English communication skills, and availability for 20–40 hours per week.

Key Skills: C++, Systems Programming, Full-Stack Development, Machine Learning Operations, Data Pipelines, Data Annotation, Data Validation, Quality Control, Backend Services, Machine Learning Frameworks, Inference Runtimes, Hardware Acceleration, Distributed Systems, Performance Profiling, Model Evaluation, Production Systems

Benefits: Fully Remote Work, Flexible Schedule, Freelance Autonomy, Potential for Ongoing Engagement