Top Remote AI Engineer Jobs

Lead the design and implementation of GPU compute clusters for AI and HPC workloads, managing infrastructure and optimizing performance.

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

Lead strategic partnerships with ISVs in AI infrastructure, ensuring optimization of NVIDIA technologies across software layers. Collaborate with teams to drive product and go-to-market strategies.

The role involves designing foundation models, contributing to large-scale training infrastructures, prototyping experiments in AI domains, and mentoring junior engineers.

Develop advanced C++/CUDA libraries for AI storage infrastructure, work with Linux kernel internals, and optimize performance in data storage solutions.

The Senior AI Performance and Efficiency Engineer will enhance AI/ML efficiency by collaborating with researchers, building tools, analyzing performance bottlenecks, and promoting scalable solutions.

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

Lead the design, development, and deployment of AI solutions using Microsoft 365 Copilot, collaborating with stakeholders and ensuring compliance.

The Pre-Sales Technical Solutions Engineer designs and presents data and AI solutions, guiding clients on analytics architecture and machine learning to drive enterprise initiatives.

As a Senior/Principal Machine Learning Engineer, you will design and develop generative AI models, lead technical vision, and mentor a team, focusing on AI-driven solutions for the AEC industry.

Design and implement conversational AI systems, optimize prompts for large language models, and integrate with backend systems while collaborating across teams.

The AI/ML Engineer will architect, maintain data pipelines, develop AI applications, and optimize distributed systems for fraud detection and prevention.

Lead the architecture and implementation of AI systems, integrating LLMs, mentoring engineers, and ensuring compliance in a high-impact role.

As a Junior AI/ML Engineer, you will work on generative AI applications, traditional ML projects, and MLOps, under the mentorship of senior engineers.

The Senior Math Libraries Engineer will design, develop, and optimize HPC software for AI and matrix operations, while leading projects and mentoring. Collaboration with various teams and technical leadership are key responsibilities.

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

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

The role involves designing and maintaining infrastructure for large-scale AI systems, enhancing system efficiency, and optimizing reliability metrics.

The role involves enhancing high-performance AI and networking environments, collaborating on infrastructure benchmarks, and mentoring teams in deep learning implementations.

The role involves developing technical content, engaging with engineering teams, conducting competitive analysis, and leading go-to-market execution for AI inference products.

The role involves designing and optimizing HPC and ML frameworks, developing software for generative models, and collaborating with various teams to improve performance.

As a Conversational AI Bot Developer, you will design, develop, and implement AI self-service applications while collaborating with clients and managing multiple projects.

NVIDIA seeks an engineer to develop and optimize algorithms for AI workloads using the Megatron Core and NeMo Framework, focusing on large language models. Responsibilities include performance tuning, model training, and contributing to open-source projects.

The AI Solution Engineer will architect and deliver AI solutions, lead technical discussions, and develop proof-of-concepts for customers, focusing on pre-sales engagements to demonstrate AI capabilities.

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