Top Remote C++ Jobs in Houston, TX

Design and develop motion planning software and algorithms for self-driving vehicles, collaborating with engineers and researchers while maintaining progress on long-term goals.

As a Distributed Systems Engineer, you will architect and build scalable data infrastructure and lead cross-functional projects at Netflix.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

Design, develop, and maintain cloud gaming infrastructure, optimizing performance for hardware and network efficiency while leading complex software projects.

Develop and deploy machine learning models for real-time ad systems, optimizing inventory management, targeting, and campaign effectiveness for Netflix's advertising platform.

The Staff Backend Engineer will lead the development of OXIO's telecom platform, focusing on backend systems, architecture, and scalable solutions. They will utilize multiple languages and cloud services while collaborating with stakeholders to innovate telecom apps.

Seeking talented Backend Software Engineers to develop solutions for large scale problems and manage project deliverables in machine learning infrastructure.

Design and develop a C++-based system for simplifying and accelerating computing in DL and HPC, alongside evaluating performance and improving library quality.

Develop compute infrastructure for robotics research, manage large compute jobs, optimize GPU utilization, and collaborate on scalable training pipelines.

Responsible for building scalable microservices and data pipelines, mentoring junior engineers, and ensuring data quality for ML training.

The Engineer will enhance developer productivity by creating and maintaining tools for the software development lifecycle, collaborating with teams to improve workflows, and ensuring efficient development processes.

The Backend Engineer will develop observability products, drive feature development, mentor teammates, and enhance engineering standards within the Release Monitoring team.

Develop, maintain, and deploy quantum applications software tools for real-world use cases while collaborating with internal and external partners.

Lead the design and prototyping of generative AI experiences and enhance user experience for Shield AI's Hivemind product line by collaborating with technical leads, conducting user research, and driving software development best practices.

The Senior Software Engineer will develop, test, and debug low-level Windows kernel features, improving product stability and user experience while addressing complex technical challenges.

Canonical seeks open-source enthusiasts to optimize Ubuntu for new silicon technologies, collaborating with teams and customers to enhance software quality and performance across various platforms.

The Senior Applications Engineer will work with research teams globally to adopt GenAI software, optimizing AI models, and providing engineering feedback on improvements for scientific research.

Collaborate with engineering teams to launch NVIDIA HGX GPU Accelerated Server Platforms. Responsibilities include planning tests, optimizing production, and improving product quality.

The Senior Software Architect will design and implement communication technologies, improve performance for AI and HPC workloads, and lead innovative GPU communication solutions.

Develop highly optimized inference framework for AI networking, utilizing GPU Kernels and RDMA cards. Engage in next-gen performance-oriented solutions.

Design and implement OpenBMC Firmware for NVIDIA's GPU Server platforms, focusing on performance optimization, coding, and collaboration with hardware teams.

The role involves designing and implementing security controls for AI services, conducting security assessments, driving technical security initiatives, and providing mentorship to engineering teams.

The Staff Software Engineer, Capacity Engineering will optimize ML infrastructure, manage hardware capacity for ML models, and improve operational efficiency while collaborating across teams.

Lead and mentor on large-scale HPC systems, develop GPU-accelerated solutions, support researchers, and optimize performance for AI workloads.

Design and implement protocols and algorithms for high performance computing systems, focusing on performance optimization and collaboration with hardware teams.